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Racial disparities in mycosis fungoides (MF) have been described historically, but their persistence in the contemporary era of diagnosis and care remains incompletely characterized. To address this gap, we evaluated survival disparities by race and socioeconomic status (SES) and assessed temporal trends in outcomes. To this end, we used the Surveillance, Epidemiology, and End Results (SEER)-22 database (2000-2021) to identify 13,694 patients with MF. Overall survival (OS) was assessed with Kaplan-Meier analyses and multivariable Cox proportional hazards models. Building on these traditional analyses, we also developed registry-based prognostic models using routinely collected variables with internal validation and geographic/registry-based external validation in a non-overlapping SEER registry subset. Across the study population, the overall 1-, 3-, and 5-year OS rates were 96.8%, 90.8%, and 85.8%, respectively. Survival was lower among Black and American Indian/Alaska Native (AI/AN) patients and highest among Asian/Pacific Islander (API) patients (5-year OS: 85.3% White, 82.7% Black, 92.9% API, 82.1% AI/AN). In multivariable adjusted analyses, Black race remained independently associated with higher mortality, whereas API race was associated with better survival. OS improved modestly in the post-2010 period overall, with a statistically significant improvement among White patients, while changes within other racial groups were not statistically significant. Importantly, lower SES independently predicted worse survival, and Black and AI/AN patients were disproportionately represented in lower-income quartiles; a similar SES distribution pattern was also observed in the National Inpatient Sample. In an integrative Cox model, Black or AI/AN race, older age, male sex, advanced stage, and lower SES independently predicted worse survival. Taken together, these findings indicate persistent racial and socioeconomic inequities in MF survival in the contemporary era. Interpretable prognostic models based on routinely collected variables may therefore support individualized risk stratification and inform efforts to improve equity in MF care.