University dropout is costly, making it a policy priority to identify factors that predict dropout. Using a survey experiment with incoming first-year students linked to long-run administrative outcomes, we assess which information improves dropout prediction beyond standard university records. A small number of targeted, study-specific survey items---especially motivation and expectations about degree completion---substantially improve predictive performance. By contrast, widely used measures