Examiner Steven W Crabb has allowed 236 of 287 decided applications (82%) in Computer Architecture, Software, and Information Security.
Steven W Crabb has a pooled allowance rate of 82% across 287 disposed applications in Technology Center 2100 (Computer Architecture, Software, and Information Security). His public record spans 3 art units: 2123, 2129, and 2148. The allowance rate ranges from 79% to 88% across these art units. This aggregate figure represents applications that were either allowed or abandoned; pending applications are excluded from the calculation. The pooled rate reflects his overall record across all three art units combined and does not predict outcomes in any specific application.
A pooled record aggregates an examiner's decisions across multiple art units into a single allowance rate. This aggregate describes the past record and is not a prediction of any specific application's outcome. The range (79% to 88%) shows variation across individual art units, but the pooled 82% represents the combined historical performance. Aggregate statistics describe correlations in past data only and carry no causal implication for any future prosecution.
These are aggregate statistics from this examiner's past public record — not predictions about any specific application. The per-art-unit figures below show how the record varies across art units. Our approach to patent prosecution →
Each section benchmarks this examiner against that art unit's average. Figures are this examiner's own public record within the art unit; the overall rate above pools them.
Primarily examines neural-network / biological-model computing, and machine learning.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 63 decided applications with an interview and 93 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 55 decided applications with an interview and 50 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Based on 26 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Methodology. This page pools every art unit in which Examiner Steven W Crabb has a public record within Technology Center 2100. Statistics are computed from publicly available USPTO records, refreshed on a recurring schedule. This page's data was last updated June 25, 2026. The overall allowance rate is total allowed divided by total decided applications (allowed plus abandoned) across all art units — not an average of the per-art-unit rates; pending applications are excluded. Figures are rounded for display. Pooled sample: 287 applications.
Lynch LLP is not affiliated with, endorsed by, or sponsored by the United States Patent and Trademark Office. Examiner statistics are derived from publicly available USPTO data.
These statistics describe past examiner behavior and do not predict the outcome of any particular application. Past results do not guarantee future outcomes. Where this page compares an examiner's allowance rate to an art-unit average, that comparison is a factual description of the public record, not a characterization of any individual examiner's conduct or competence.
This page is for general informational purposes and is not legal advice. No attorney-client relationship is formed by viewing it. Full disclaimers →
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