We present results and conclusions stemming from the application of various optimization methods on an academic database. The goal is to provide a tool for our client to use to predict the best prospective students based on data gathered pre-registration. We applied several optimization programs to our database. The methods will be compared and contrasted based on accuracy and transferability of results to future student data. We also analyze the general "goodness" of the database itself, and propose possible improvements that will aid in better classification.