The decision to choose a program of study is a major one since a student must commit to it for four years, until graduation. Hence it is a crucial decision for academic as well as future career success. Despite this, students often make academic choices without careful thought mainly due to lack of proper advice and support. In this paper, we use four methods that utilize students' data such as their performance in high school, college placement test, and standardized IELTS exam to recommend a college program as well as predict the students GPA in those programs. Using the four methods utilizes the advantages of each of them and provides insight into the reason for the recommendation. The four methods that we used, evaluated, and compared are Decision Trees (DT), Neural Network (NN), K-Nearest neighbor (KNN), and Linear Regression (LR). To the best of our knowledge, this is the first study that utilizes and compares the different approaches.