Data classification means categorization of data into different category according to rules. This paper is to extract a kind of "Structure" from a sample of objects. To rephrase it better to learn a concise representation of these data. Present research performed over the classification algorithm learns from the training set and builds a model and that model is used to classify new objects. This paper discusses one of the most widely used supervised classification techniques is the decision tree. And perform own decision tree evaluate strength of own classification with performance analysis and results analysis.