Study of research progress in the academic domain is challenging for student’s academic performance in Tamil Nadu higher education sectors. The data collected from various engineering colleges augment this issue for supporting the results in this direction. Here in this paper we address this issue positively with the help of the educational data mining. The Classification method as one of the major data mining methodologies can be applied effectively for this purpose. The main focus of this paper is to check the learning algorithms for classification such examples based on selected dataset for student’s academic performance. The main intention in this context is to deal with available data set for high accuracy. For this purpose, AdaboostM1, Bagging and Dagging models are built using an open source mining Weka under supervised learning algorithms. It is necessary to reduce the error before constructing the final models and thus the varying the parameters and number of iterations for training is carried out.