Motion to Dismiss Grant Rates by Federal District Judge

Informational only — not legal advice. This guide is general information about litigation analytics, not legal advice, and does not create an attorney–client relationship. GavelSight is not a law firm. Judicial analytics describe historical patterns in the public record; they do not predict the outcome of any specific case. Always exercise independent professional judgment.

What a Motion to Dismiss Grant Rate Actually Measures

A judge's motion to dismiss grant rate is the percentage of Rule 12(b)(6) motions that the judge grants, fully or partially, over a measured period. It sounds simple, but the number hides enormous complexity.

A "60% grant rate" might mean this judge dismisses most weak cases early — a boon for defendants who want to avoid discovery costs. Or it might mean the judge gets an unusual volume of poorly pleaded complaints from pro se litigants, inflating the number. Without understanding the composition of cases behind the statistic, the raw number can mislead.

Grant rates become meaningful when you can filter them: by case type (employment, contract, civil rights, securities), by time period (recent 3 years vs. career), and by outcome granularity (full grants vs. partial grants vs. grants with leave to amend). A single aggregate number is a starting point, not a strategy.

Rule 12(b)(6) vs. Other Dismissal Bases

Federal Rule of Civil Procedure 12(b) lists seven bases for dismissal. A motion to dismiss "grant rate" that lumps them all together is nearly useless for litigation strategy:

• 12(b)(1) — Lack of subject matter jurisdiction: These are jurisdictional questions. A high grant rate here says nothing about how the judge evaluates claims on the merits.
• 12(b)(2) — Lack of personal jurisdiction: Fact-specific to the defendant's contacts with the forum. Again, not indicative of merits tendencies.
• 12(b)(6) — Failure to state a claim: This is the one litigators care about. It tells you how aggressively the judge polices pleading sufficiency under Iqbal/Twombly.

When you're evaluating whether to file a motion to dismiss or how to defend against one, you need the 12(b)(6) rate isolated from other dismissal bases. Platforms that report a combined "dismissal rate" across all 12(b) grounds are giving you noise, not signal.

Why Grant Rates Vary Dramatically Between Judges

Judicial Philosophy

Some judges read Iqbal/Twombly's plausibility standard strictly — if the complaint doesn't contain specific factual allegations supporting each element of the claim, it gets dismissed. Others apply the standard more liberally, especially in cases where the plaintiff doesn't yet have access to the evidence needed to plead with specificity (employment discrimination, for example, where the employer controls the relevant documents).

These philosophical differences are real, measurable, and stable over time. A judge who is strict on pleading sufficiency in 2023 is very likely still strict in 2026. This is the core of what judge analytics measures.

Caseload Composition

A judge in the Southern District of New York sees a different mix of cases than a judge in the Western District of Texas. Securities fraud, complex commercial litigation, and patent cases have different baseline dismissal rates than immigration cases or civil rights claims. Comparing raw grant rates across districts without controlling for case mix is comparing apples to aircraft carriers.

Circuit Culture

Appellate circuits develop their own interpretive patterns. A district judge in the Fifth Circuit operates under different precedent than one in the Ninth Circuit. Some of the variation in district judge grant rates reflects circuit-level doctrinal differences, not individual judicial philosophy. Good analytics tools control for this — or at least flag it.

The Problem with Raw Statistics

Partial Grants

Most MTD analytics report binary outcomes: granted or denied. In reality, partial grants are common. A judge might dismiss three of five counts and let the remaining two proceed. Is that a "grant" or a "denial"? The answer matters: if you're the plaintiff, two surviving counts mean discovery proceeds. If you're the defendant, three dismissed counts significantly narrow the case.

GavelSight treats partial grants as distinct outcomes rather than forcing them into a binary framework. When a judge grants in part and denies in part, that's recorded as what it is — a partial grant — so you can see the judge's actual behavior rather than a simplified version of it.

Stipulated Dismissals

Cases dismissed by stipulation — where the parties agree to dismiss — can inflate a judge's "dismissal rate" if not properly filtered. These aren't judicial decisions; they're party agreements. Any analytics platform that doesn't distinguish stipulated dismissals from contested rulings is inflating the numbers.

Case-Type Bias

Certain case types have inherently higher or lower dismissal rates. Pro se prisoner litigation, for example, has a very high dismissal rate across all judges. If a judge handles a disproportionate share of pro se cases, their aggregate grant rate will be higher than a judge in the same courthouse who primarily handles commercial litigation — even if their underlying judicial philosophy is identical.

How to Interpret Grant Rate Data Responsibly

Sample size: A grant rate based on 5 rulings is anecdotal, not statistical. A grant rate based on 50 rulings in the same case type is a genuine signal. GavelSight enforces minimum sample thresholds — we won't surface a tendency when the data is too thin to support it.

Time period: A judge's tendencies can shift over time, especially after a notable reversal on appeal or a change in circuit precedent. A 10-year aggregate rate may mask a meaningful recent shift. Look for tools that let you filter by time period.

Case type filter: A 45% overall MTD grant rate means almost nothing. A 45% MTD grant rate in employment discrimination cases, based on 30 rulings over the past 3 years, is actionable intelligence. Always look for the case-type breakdown.

Where to Find MTD Data

Manual PACER research remains an option but is time-intensive. You'd need to identify relevant docket entries, pull individual opinions, read each one to determine the outcome, and tabulate the results yourself. For a thorough analysis, this can take 10-20 hours per judge.

Structured analytics platforms accelerate this dramatically. Westlaw Edge Litigation Analytics provides motion-level data for judges with deep federal coverage. Lexis+ Context offers similar capabilities as an add-on. Trellis focuses on state courts. GavelSight provides federal judge analytics with transparent methodology at $79/seat/month.

The key differentiator across platforms is transparency. Can you see the raw data behind the number? Can you inspect the methodology? Can you verify how partial grants were counted? If the platform gives you a number without showing its work, you're trusting a black box with your litigation strategy.

How GavelSight Surfaces Motion-Level Analytics

GavelSight's approach to motion analytics is built on three principles:

1. Transparency: Every motion-level statistic surfaces its sample size, time period, data source, and methodology. You can inspect the data behind the number.
2. Granularity: Motion outcomes are broken down by case type, motion type, and outcome (full grant, partial grant, denial, grant with leave to amend). No forced binary classifications.
3. Honest uncertainty: When the sample size is too small or the data is ambiguous, we say so. A confidence interval that's honest about its width is more useful than a precise-looking number that hides its uncertainty.

Every judge profile in our directory includes case-type tendency data. For subscribers, this expands to full motion-level analytics with prediction scores. Read about our methodology for the technical details.

What This Means for Your Litigation Strategy

The Go/No-Go Decision on Filing a Motion to Dismiss

If your assigned judge grants motions to dismiss in employment cases at 25% — well below the district average — that shapes your calculus. For defendants, a motion to dismiss becomes a lower-percentage play, and resources might be better directed toward early discovery or settlement posture. For plaintiffs, a low grant rate is reassuring but shouldn't breed complacency in pleading quality.

Tailoring Your Arguments

Judges with high grant rates on specificity grounds respond to arguments about the complaint's factual deficiencies. Judges with low grant rates may be more receptive to arguments about legal sufficiency — framing your motion around the legal theory rather than the factual allegations. Reading the judge's recent MTD opinions (which GavelSight links directly) reveals what arguments land.

Judge research doesn't tell you whether you'll win. It tells you how to fight.

Related guides: How to Research Judge History · SJ Grant Rates by Judge · Time to Ruling Data