Abstract: : In healthcare and bioinformatics, the classification of breast cancer has become an area of concern since this is the second largest explanation for women deaths from cancer. Breast cancer can be analysed using a biopsy in which tissue is removed and microscopically examined. The issue diagnosis is dependent on the qualification and expertise of histopathologists who are interested in irregular cells. If the histopathologist is not well qualified or experienced, though, the diagnosis may be incorrect. In recent times there is an interest in the experiment in creating a solid pattern recognition system to increase diagnostic accuracy, as proposed in image processing and the machine learning domain. We will use this image extraction technique in order to classify breast cancer using historologically-related pictures to benign and malignant using form features and machine learning approach. We will preprocess this picture with historopathological image, after that we can extract features and identify the final results by using techniques of SVM and Naive Bayes classification.Keyword: Histopathological image classification, breast cancer diagnose, feature extraction, SVM classification, Naive Bayes Classification.