NIH R01 Success Rates & Paylines

NIH does not have one “success rate.” It has 27 Institutes and Centers (ICs), each running its own budget, its own portfolio priorities, and — historically — its own payline. An R01 that would be funded at NINDS in a given fiscal year might miss the payline at NCI, and vice versa. Treating NIH as a single funding-rate number, the way many applicants treat NSF’s agency-wide figure, produces a misleading picture. This guide covers the two metrics researchers routinely confuse (payline and success rate), where NIH itself publishes the authoritative numbers, why institute-level variation is structural rather than incidental, and a major November 2025 policy shift that changes how several ICs now talk about funding likelihood at all.

A note on numbers before you read further: R01 paylines and success rates change every fiscal year, differ by IC, and — as of late 2025 — several ICs are actively moving away from publishing a percentile payline at all (see below). Any specific percentile or percentage quoted anywhere, including in older CASRAI pages, secondary funding-consultant sites, or this guide’s own illustrative examples, should be treated as a snapshot in time. Always confirm the current figure directly against the awarding IC’s own funding-strategy page or NIH’s own success-rate tables before using a number to plan a submission.

Payline vs. Success Rate: Two Different Metrics

These terms get used interchangeably in hallway conversation, but they measure different things and answering “how likely am I to get funded” correctly depends on knowing which one you’re looking at.

Payline: a percentile-rank threshold that an IC sets, typically at the start or partway through a fiscal year, as a planning guideline for which applications it expects to fund without further review. An application’s priority score is converted to a percentile rank relative to other applications reviewed by the same study section over a rolling period; scoring at or better than the published payline is a strong (but not absolute) signal of funding. ICs retain discretion to fund outside the payline through mechanisms like select pay, exception pay, or bridge funding, and to decline funding inside the payline in rare cases. No single NIH-wide payline exists — it is set per IC, and historically even varies by activity code and investigator status (many ICs, including NIAID and NINDS, have published a separate, more generous payline for Early Stage Investigators).
Success rate: a retrospective, backward-looking statistic — the number of applications funded in a fiscal year divided by the number of applications reviewed (or sometimes, the number of unique applications submitted, counting resubmissions differently depending on the table). It is reported after the fact, per IC, per activity code, and NIH also publishes it in aggregate. Success rate reflects everything that happened that year — how many applications came in, how the budget was allocated, how much of the portfolio went to non-competing renewals versus new awards — not a forward-looking cutoff.

The practical distinction: a payline is a planning tool you can compare your own percentile score against before a funding decision; a success rate is a historical ratio useful for calibrating expectations and benchmarking an IC’s overall competitiveness, but it doesn’t tell you whether your specific score would have been funded. A study section with an unusually strong pool of applications in a given round can push the effective cutoff for funding tighter than the published payline would suggest, and some ICs fund a meaningful share of their portfolio through non-payline pathways (program priority, bridge awards, high-priority initiatives), which further separates the two numbers.

Why R01 Funding Rates Differ So Much by Institute

NIH is not one funding pool — it is 27 ICs (e.g. NCI, NIAID, NHLBI, NINDS, NIGMS, NIMH, and others), each appropriated its own budget by Congress and each managing a distinct portfolio of research areas, mechanisms, and strategic priorities. That structure is the primary reason institute-level variation exists at all:

Budget size relative to application volume: a large IC with a comparatively smaller applicant pool in its scientific area can sustain a higher funding rate than a smaller IC receiving a disproportionate volume of applications in a hot research area.
Portfolio balance decisions: ICs vary in how much of their competing-grant budget they commit to non-competing renewals (multi-year commitments from prior awards) versus new and competing R01s in a given cycle, which mechanically changes how much is left for new paylines.
Mechanism mix: some ICs run large program-project or center-grant mechanisms (e.g. P01 program projects, cancer center support grants) alongside R01s, which draws down budget differently than an IC that is more R01-heavy.
Different approaches to publishing a payline at all: not every IC uses the same payline philosophy. Some (NHLBI, NINDS, NIAID) have historically published a numeric percentile payline, often with a separate, more generous line for Early Stage Investigators. NIGMS has taken a structurally different approach — it has generally not published a traditional percentile payline, instead describing funding decisions as weighing percentile score alongside investigator support level and portfolio balance, partly because its flagship MIRA (R35) mechanism funds an investigator’s whole research program rather than a single specific-aims project, which weakens the logic of a single project-level percentile cutoff. NCI has published payline-style percentile goals in some years while explicitly not publishing one for other cycles, awarding in percentile order as funding allows instead.

This means a general statement like “NIH funds about X% of R01 applications” is true only as an aggregate, and it obscures wide variation underneath it. Two applications with identical percentile scores submitted to two different ICs can have meaningfully different funding odds.

Where NIH Publishes Its Own Success Rate Data

Because paylines and success rates change every fiscal year and differ by IC, the only reliable approach is to go to NIH’s own current data rather than rely on a number quoted in an article (including this one) that may already be out of date by the time you read it. NIH’s Office of Extramural Research (OER) is the authoritative source:

NIH RePORT (report.nih.gov) publishes NIH’s official success rate tables, broken out by IC, fiscal year, and activity code (R01, R21, etc.), including separate tables for competing applications and awards. This is the primary source for retrospective success-rate figures.
NIH RePORTER (reporter.nih.gov) is the searchable award database — useful for looking at what an IC has actually funded (mechanism, amount, institution) in recent cycles, complementing the aggregate success-rate tables with actual award-level detail.
Individual IC funding-strategy or “current funding policy” pages (hosted on each institute’s own site, e.g. nigms.nih.gov, cancer.gov for NCI, niaid.nih.gov, ninds.nih.gov) are where an IC publishes its current-year payline or funding-philosophy statement, when it publishes one at all. These pages are the right place to check for a specific IC’s current-year guidance — not an aggregated third-party table, which can lag or misstate IC-specific nuance.
NIH’s Office of Extramural Research (grants.nih.gov) hosts general OER policy guidance, including notices announcing agency-wide funding-strategy changes (see the next section).

CASRAI’s own Research Grant Funding Statistics guide covers this same navigational problem more generally across NIH, NSF, and other funders, plus the terminology needed to read a success-rate table correctly (competing vs. non-competing, application vs. award counts, etc.) — useful background if you’re building a table from NIH RePORT data yourself.

The November 2025 Shift Away From Published Paylines

NIH announced via its Extramural Nexus News page, in a notice titled “Implementing a Unified NIH Funding Strategy to Guide Consistent and Clearer Award Decisions” (dated November 21, 2025), that its Institutes and Centers “will not rely on funding paylines in developing pay plans” going forward. The stated direction is to weigh peer-review scores against institute priorities, strategic plans, and budget considerations rather than a fixed, published percentile cutoff.

Several IC-specific pages already reflect this shift in their own naming and framing — for example, at least one IC’s page formerly titled around “paylines” has been retitled to “Funding Policies and Considerations,” consistent with the move away from a single published percentile number as the primary planning signal. Because this is a genuinely recent, still-unfolding policy change, implementation appears to vary by IC and by fiscal year rather than applying uniformly and immediately across all 27 ICs. Do not assume that because one IC has stopped publishing a traditional payline, all have, or that the change is final and permanent — confirm against the specific IC’s own current guidance page before making submission-timing or budget decisions based on payline expectations.

How Individual Institutes Have Approached Paylines and Success Rates

The pattern differs enough across ICs that it’s worth understanding the general shape of the differences, even without citing specific current numbers here (see the sourcing note above for why). CASRAI maintains institute-specific reference pages that track each IC’s approach in more depth:

NHLBI Payline — the National Heart, Lung, and Blood Institute’s approach to setting and publishing an R01 payline.
NINDS Payline — including its historical practice of publishing a separate, more generous extended payline for Early Stage Investigators.
NIAID Payline — NIAID has historically distinguished an early-fiscal-year “interim” payline from a later “final” payline and maintained an archive of final paylines by year.
NIGMS Payline — NIGMS’s structurally different, non-percentile-cutoff approach, tied to its MIRA (R35) mechanism.
NCI Funding — the National Cancer Institute’s funding mechanisms, including its history of publishing percentile-goal paylines in some fiscal years and not in others, and its distinct “bypass budget” appropriations process under the National Cancer Act of 1971.

The common thread across all of them: check the specific IC’s own current page, for the specific fiscal year and activity code you care about, rather than treating any one institute’s approach as representative of NIH as a whole.

How to Use This Data When Planning a Submission

Identify the right IC(s) first. Many R01 topics could plausibly be assigned to more than one institute; if your study section or dual-assignment history spans ICs with different funding postures, that matters for planning.
Pull the current fiscal year’s data directly from the IC and from NIH RePORT, not from a remembered number or an older article — paylines and success rates move year to year, and, per the section above, the underlying mechanism (a published percentile line at all) is itself changing at some ICs.
Distinguish “my percentile score” from “will I be funded.” A percentile score at or better than a published payline is a strong positive signal, not a guarantee; scoring outside it does not automatically mean no funding, given select-pay and exception-pay discretion.
Use success rate for calibration, not prediction. A retrospective success rate tells you how competitive an IC’s overall pool was last year — useful for setting expectations about resubmission likelihood or for comparing ICs — but it is not a probability estimate for any single application.
Talk to your program officer. For an application close to a payline, or at an IC that has moved away from publishing one, your assigned NIH program officer is the most current and application-specific source of guidance — closer to real time than any published table.

NIH vs. NSF: Two Different Funding-Rate Pictures

Researchers who submit to both NIH and NSF are effectively navigating two different funding-rate models. NSF publishes a clearer agency-wide success rate (recently around the high-20s percent) alongside directorate- and division-level rates that vary from single digits to over 40%, but it does not use a payline/percentile-threshold system comparable to NIH’s — see CASRAI’s NSF Grant Success Rates guide for the NSF-side counterpart to this page, including how to read NSF’s own Funding Profile and program-level data. NIH’s system, by contrast, has historically centered on the payline as a forward-looking planning signal at the IC level — a mechanism NSF doesn’t use in the same way — which is now itself in flux following the November 2025 policy shift described above.

Frequently Asked Questions

Is there one NIH-wide R01 success rate?

NIH publishes an aggregate figure, but it averages across 27 ICs with materially different budgets, portfolios, and (historically) paylines. An aggregate number is a poor predictor for any specific IC; use IC-specific data from NIH RePORT and the awarding institute’s own page instead.

What’s the difference between a payline and a percentile score?

A percentile score is assigned to your specific application, ranking its priority score against other applications reviewed by the same study section over a defined period. A payline is the threshold an IC sets, in advance, for which percentile ranks it expects to fund. Your percentile score is compared against the IC’s payline to gauge funding likelihood, but they are not the same number.

Why did NIH stop publishing paylines at some institutes?

NIH announced in November 2025 (via its Extramural Nexus News page) a “Unified NIH Funding Strategy,” under which Institutes and Centers are directed not to rely on funding paylines when developing pay plans, instead weighing peer-review scores against institute priorities and budget considerations. Implementation appears to be rolling out unevenly across ICs and fiscal years rather than as a single uniform switch — check the specific IC’s current guidance.

Where can I find NIH’s official R01 success rate tables?

NIH RePORT (report.nih.gov) publishes NIH’s official success-rate tables broken out by Institute/Center, fiscal year, and activity code. NIH RePORTER (reporter.nih.gov) complements this with a searchable database of actual awards. Individual IC websites publish current-year payline or funding-policy statements when available.

Does a lower payline mean an institute is “harder” to get funded at?

Generally a lower (more restrictive) payline percentile does indicate a more competitive funding environment at that IC in that cycle, but paylines aren’t perfectly comparable across ICs because they interact with different portfolio structures, mechanism mixes, and (as of the November 2025 shift) different degrees of continued reliance on a published percentile threshold at all. Success rate and payline should be read together, and always for the specific fiscal year in question.