Many women of mid-age suffer with breast cancer. Study says, this disease is the major reason behind the mortality. Since this became a main issue, lot of researches were done in identifying the cause of this. If a woman can predict the possibility of this disease based on her other characteristics, she can be vigilant and can treat early. The identification of malignancy of this disease is the need of the hour. This can be achieved by using classification and prediction algorithms. This paper implements different machine learning techniques for this aim and analyses efficiency of those algorithms. The analysis was made based on Wisconsin breast cancer dataset (WBCD)