Universities are interested in predicting the paths of students, thus identifying which students will join particular faculty and which students will require a large number of debates. For Universities whose goal is to contribute to the improvement of educational quality process, the success of selection of the student best fit path is the subject of a continuous analysis. Therefore, the prediction of students' path is crucial for Universities, because the best fit path that match with the ability of students' needs. All participants in the educational process could benefit by applying data mining on the data from the higher education system (Fig.1). Since data mining represents the computational data process from different perspectives, with the goal of extracting implicit and interesting samples, trends and information from the data, it can greatly help every participant in the educational process in order to improve the understanding of the teaching process, and it centres on discovering, detecting and explaining educational phenomenon’s .