This article describes statistical research on the academic performance of student-athletes in college sports programs. We describe several statistical models used in the prediction of academic success defined by college persistence and graduation. Using longitudinal data on the academic performances of about 3,000 student-athletes in NCAA Division I collegiate sports programs, we formulate logit and multilevel logit statistical models for the prediction of graduation rates. These prediction models are based on academic, demographic, and athletic variables, and are used to account for differences in both the students and the colleges. These results show (1) moderate but significant relationships between precollege academic characteristics and college graduation, (2) small but significant differential validity of prediction between major student-athlete groups, (3) notable college-level variance in the average graduation rate, (4) small but significant within-college relationships between precollege academic characteristics and college graduation, and (5) differences between colleges accounted for by institutional graduation rates. We highlight statistical issues about the application of logit and multilevel models and discuss substantive issues about the current implications of these results.