The purpose of this investigation was to develop an ultra-short questionnaire that reliably predicted re-enrollment. Two binary stepwise logistic regressions were performed using re-enrollment status as the criterion. The first regression, conducted with a subsample of 4619 undergraduates, reduced 32 items drawn from the College Persistence Questionnaire to seven statistically significant predictors. The second regression, calculated on the seven predictors in a different subsample of 4620 students, yielded five statistically significant items that explained 20% of the variance. Entering the remaining 27 items only increased the explained variance by 2%. The five items were combined to form an assessment tool called the Brief Index of Student Retention (BISR). Additional analyses indicated that with one minor exception, the predictability of the five retained items did not depend on the students' sex, academic classification, or their parents' education level. Strategies for using the instrument to identify at-risk students and improve retention are discussed.