The Breast cancer is one of the leading cancers for women in world countries including India. It is the second most common causes of cancer death in women. The high incidence of breast cancer in women has increased significantly in the last few years. Detecting cancer in the later stages, leads to very complicated surgeries and the chances of death is very high nowadays. Early detection of Breast Cancer helps in less complicated procedures and early recovery. Many tests have been found so as to detect cancer. Some of those tests are mammography, ultrasound etc. Mammography is a method that helps in early detection of Breast Cancer. But finding the mass and its spread from mammographic images is very difficult. Expert radiologists were needed for accurate reading of a mammogram image, and analyses have been for k- Means algorithm which helps for easy detection and extraction tumor area. The mammography image helps to provide some criteria in order to help the physicians to decide whether a certain disease is abnormal or normal. This research work is to identify the breast cancer tumor area and find its affected region by splitting the images into five clusters. The tumor area has been identified in the last cluster and classified with the help of decision tree algorithms J48 and CART.