Cortez, et al. proposed a Bayesian Networks based approach for student Data Classification [6]. The research work implement binary data classification, 5 levels Data classification and a regression based analysis for predictive performance calculation of classification algorithms and descriptive knowledge analysis for better quality management in educational organization. Qasem, et al. discussed a decision tree approach based on C4.5, id3 and Naïve Bayes. The research work proposed a Cross Industry Standard Process for Data Mining (CRISP-DM) based classification model for student performance evaluation Model [7].