Studying hate crime clearance rates provides an opportunity to uncover the factors that influence police effectiveness for a relatively new legal category—one that was designed ostensibly to protect minorities, and that may pose unique challenges for police reporting, defining, and investigation. Using multiple years (2005-2010) of data from the National Incident-Based Reporting System (NIBRS), we estimate event history models to compare the incident-level predictors and relative probability of arrest for hate and nonbias crimes. As an aggregate category, we find hate crimes are less likely to clear than nonbias crimes. However, the most prototypical hate crimes—White-on-non-White incidents motivated by racial and ethnic bias—are as likely to clear as the most successfully cleared nonbias crimes. Our results suggest that only hate crimes that fit popular constructions of “normal victims and offenders” receive investigative outcomes comparable with otherwise similar nonbias offenses.