Artificial neural networks (ANNs) consists of computational neurons or processing elements are linear mathematical model which abstract away the complex biological model and its aim is good, human like predictive ability. Artificial intelligence tries to simulate some properties of biological neural networks. In this study on the basis of previous dataset the in symptoms data are applied to a supervised back propagation artificial neural network learning process to find out the predictive outcome which is better than logistic regression (LR) process. As in most cases ANN is an adaptive system that changes its structure on the basis of internal and external information, the predictive result is more accurate than any other processes.