Despite the prevalence of sexual violence (SV), there is limited understanding of community-level predictors of SV. Using structural equation modeling, I examined the relationships between police-reported SV crime, non-sexual violent crime, alcohol outlet density, neighborhood disadvantage, and gender inequality at the county level across 14 US states (940 counties). I found that non-sexual violent crime, alcohol outlet density, percent of single-parent households, and education gender inequality were positively associated with SV crime. Further, poverty rates, percent of the population receiving public assistance, and employment gender inequality were negatively associated with SV crime. The final model demonstrated that when poverty rates were one percent higher, SV crime rates were two-percent lower; when the rates of those receiving public assistance were one-percent higher, SV crime rates were four-percent lower; and when the rates of single-parent households were one-percent higher, SV crime rates were three-percent higher. Further, when men’s employment rates were twice that of women’s, SV crime rates were 73-percent lower; and when men’s educational attainment rates were twice that of women’s, SV crime rates were 32-percent higher. Lastly, when non-sexual violent crime rates were one-percent higher, the SV crime rates were .3-percent higher; and for each additional alcohol outlet per 10,000 residents, SV crime rates were one-percent higher. Future preventionists and policymakers should consider these county-level characteristics in the design of prevention and intervention efforts, and future researchers should control for these county-level characteristics to reduce error and improve their ability to understand complex community-level predictors of SV.