Based on the admission information and first–year academic results collected from full–time students at Tay Bac University, this study applies classification techniques in data mining to build a prediction model for students’ academic performance. The core of the study is the decision tree model, which enables analyzing influential factors and visualizing the prediction process in an intuitive manner. After evaluation and comparison, the model with the highest accuracy was selected and used to develop a prediction support tool, contributing to academic advising and helping students achieve better performance.