Several data mining techniques are used to extract hidden knowledge in educational data to help students make a useful decision for their university orientation. Indeed, every year, students are enrolling in universities, the massive arrival of these candidates poses the thorny problem of orientation. The hidden problem behind this orientation is the lack of information concerning the possibilities of orientation; or the lack of support from the close entourage. Having developed the survey questionnaire, the authors collected 712 responses. After analyzing these data, they trained the models and measured their performance with four evaluation measures: accuracy, precision, recall and the F-score. The results of these models showed that the SVM algorithm gave 70% accuracy, the Naïve Bayes 65% Accuracy, the Neural Network 64% and the decision tree gave only 52%. This allowed SVM to be selected as the model that predicted better than the others. Finally, the authors deployed the validated model in web technology using Flask.