The paper quantizes symptom data through binary coding, divides 8 syndromes summed up by experts into excess and deficiency syndromes, values and quantizes them, and establishes the model for classification of excess and deficiency syndromes of colorectal cancer based on BP neural network and decision tree. The result shows that BP neural network classification model is more applicable for the handling of the nonlinear mapping relation compared with decision tree classification model.