Both an art and a science, enrollment projections have become a major component to effective college and university fiscal planning. With stagnant or declining state budget support for public higher education along with an increasing emphasis on revenue generation, never before has predicting the size of an entering class become more imperative. Too few students and budgets are sure to suffer; too many students and residence halls will be overflowing. This article presents several approaches to manage enrollment data for an entering class and predict enrollment yield. By examining past yield behavior coupled with trend and conversion data, a college or university will be better positioned to provide exceptionally accurate enrollment forecasts to senior administration. The authors provide pragmatic examples to empirically engage and data mine applicant pools for both first year and transfer populations in order to predict yield conversion with a greater level of confidence. Special attention will be placed on describing different statistical and mathematical techniques to predict enrollment.