Due to increasing interest in data mining and educational system, educational data mining is the emerging topic for research community. educational data mining means to extract the hidden knowledge from large repositories of data with the use of technique and tools. educational data mining develops new methods to discover knowledge from educational database and used for decision making in educational system. The various techniques of data mining like classification. clustering can be applied to bring out hidden knowledge from the educational data. In this paper, we focus on the educational data mining and classification techniques. In this study we analyze attributes for the prediction of student's behavior and academic performance by using WEKA open source data mining tool and various classification methods like decision trees, C4.5 algorithm, ID3 algorithm etc.