The project demonstrated to analyze the survivability of cervical cancer from the large data set of SEER (Surveillance Epidemiology and End Results). The data were re-sampled into 10 folds on 5 different size that were based on for three methods- artificial neural network, logistic regression and decision tree- to establish models for predicting the survivability of cervical cancer. In the meanwhile, 10-fold cross-validation was used to examine the respective models of three methods for performance comparison.