SSA Administrative Law Judge

Hon. Serena S. Hong

Last decided San RafaelJul 2026
Decisions 3,615since 2016

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Approval rates

Comparing Serena S. Hong's 67% approval rate against the 43% to 79% range of other judges whose most recent office on record is San Rafael provides context for her decision-making history. In the most recent reporting period, her 69% approval rate sits 8 percentage points above the office average of 61%. These figures are derived from a docket of 3,615 decisions on record since 2016. Aggregate rates describe past decisions, not predictions for your individual hearing.

All decisions on record SSA records since 2016
Approval rate 67%
Decisions on record 3,615
Latest SSA reporting period July 31, 2026
Metric Judge Hong San Rafael National
Approval rate 69% 61% 58%
Fully favorable 47% — —
Denials 31% — —

Office- and national-level breakdowns of fully favorable vs denial rates aren't currently published by SSA in the per-office disposition data. The judge's own breakdown is the detail we have today.

Approval rate over time

Year-over-year approval rate across Judge Hong's docket. Annual rates fluctuate with the mix of cases SSA assigns; the longer-run pattern is more informative than any single year.

Judge Hong
0%20%40%60%80%100%FY16FY26
Source: SSA OHO disposition data. Approval rate (SSA's term: allowance rate) = fully favorable + partially favorable decisions divided by total decisions, which exclude dismissals.

Decision pattern

Since 2016, Serena S. Hong's approval rate has shown a steady pattern with minor annual fluctuations. After reaching a peak of 73% in 2020, the rate adjusted to 62% in 2021 before stabilizing in the mid-60% range. The most recent fiscal year-to-date data shows a rate of 69% over 149 decisions, which aligns with your long-term average. This consistency suggests that your approach to evaluating evidence remains steady over time.

Preparing for an SSDI hearing

The guidance below applies to any SSDI hearing, not specifically to Judge Hong's bench. Judge-specific preparation guidance requires a corpus of public Appeals Council decisions involving each judge, which we haven't built yet.

  • Bring a clean treating-physician record. Longitudinal primary-care or specialist notes spanning the disability period, with consistent symptom documentation, are typically the strongest evidence at hearing. A single month's records usually aren't enough.
  • Don't rely on consultative exams alone. If your medical evidence is built primarily around a one-time CE finding, expect detailed questioning. Supplement with treating-source statements where possible.
  • Prepare for daily-activity questions. Have honest, specific answers about a typical day. Answers that conflict with the medical record (in either direction) tend to hurt credibility.
  • Expect transferable-skills probing. A vocational expert will usually testify about jobs available to someone with your limitations. Your representative should be prepared to cross-examine.

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About the San Rafael hearing office

Serena S. Hong's most recent office on record is the San Rafael hearing office, which serves you in the California region. This office maintains a bench of 8 judges with varying approval patterns. You can expect a standard hearing process where the quality of your medical evidence is the primary factor in the outcome. You can see the San Rafael Hearing Office page for the full ALJ roster.

Other judges whose most recent office on record is San Rafael

The Social Security Administration uses a workload-balancing algorithm to assign cases, meaning the judge you are assigned is essentially random. There are 8 judges whose most recent office on record is the San Rafael office. Approval rates among this group vary widely, ranging from 43% to 79% on their records since 2016. For preparation purposes, the guidance is the same regardless of which judge you are assigned.

Approval rates change with a lawyer

WITHOUT A LAWYER
1×
baseline approval rate
Unrepresented claimants
WITH A LAWYER
~3×
higher approval rate
Represented claimants

Source: U.S. Government Accountability Office, GAO-18-37. The 3× gap is a population-wide average across all judges; individual outcomes vary.

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