Cancer is a disease that makes the cells in the body grow out of control. When cancer starts in the breast, it is called breast cancer. Breast cancer is one of the major death causing diseases of the women in the world due to delays and inaccuracies in diagnosis of the disease. The high accuracy in cancer prediction is important to improve the treatment quality and the survivability rate of patients. In this paper, we hope to reduce the risk of the breast cancer at the earlier stage. So, we have propose a contain two parts: First: We use a Rough Set Theory (RST) as an efficient and intelligent technique, to analyze breast cancer dataset, evaluate approximate sets, and improve the accuracy of diagnosis with reduce redundancies, and evaluate the importance attributes of data. Second: We will construct MATLAB program to diagnosis and treatment of breast cancer depending on the decision rules which can generate by Rough Set Theory from dataset, and the information’s taken from records of patient’s data base. This system may help doctors to predict and diagnose breast cancer early, also helps in follow-up of the record and medical history of any patient.