Classification in data mining is receiving immense interest in recent times. As the knowledge is based on
historical data, classifications of data are essential for discovering the knowledge. To decrease the
classification complexity, the quantitative attributes of data need splitting. But the splitting using the
classical logic is less accurate. This can be overcome by the use of fuzzy logic. This paper illustrates how to
build up the classification rules using the fuzzy logic. The fuzzy classifier is built on by using the prism
decision tree algorithm. This classifier produces more realistic results than the classical one. The
effectiveness of this method is justified over a sample dataset.