In this paper, we are using three input attributes of training data set quoted by LB, AC, and FM to categorize as normal, suspect or pathological where NSPF variable is used as response variable. After drawing necessary analyzing into three variables we get the 19 nodes of classi cation tree and also we have measured every single node according to statistic, criterion, weights and values. The Cardiotocography Dataset applied in this study are received from UCI Machine Learning Repository.