Breast cancer treatment is one of the medical mysteries, yet unresolved challenge for medical practitioners. The key for better treatment is early diagnosis and treatment. However, even after early diagnosis and treatment, there is high chance of recurrence. By making early prognosis, thus, patients can get better treatment. Data mining, as a knowledge mining field, can contribute on better prognosis with better accuracy rate of prediction. In this report, working on WEKA software, we are trying to show on how to get a decision tree with better accuracy rate. Dealing with the Wisconsin Breast Cancer Database, collected by Dr. William H. Wolberg, University of Wisconsin Hospitals, we will discuss on how we a decision tree data mining technique gives better prediction tool.