-The most frequent cause of cancer-related mortality is breast cancer All breast lesions are not malignant, and all benign lesions do not advance to cancer. The goal is to raise the proportion of breast cancers discovered at an early stage, allowing for the adoption of more effective treatment and lowering the risks of death. Recent study has shown that Machine Learning (ML) technology can accurately diagnose Breast Cancer (BC), because effective treatment of the illness is dependent on early detection. Based on the features, several machine learning algorithms are utilized to evaluate whether a tumor is benign or malignant. The objective of this study is to diagnose the breast cancer based on 9 features using five different classification algorithms such as KNN, SVM, Adaboost, Naive Bayes and Random Forest have been compared. To achieve this objective data were collected from UCI machine learning repository. The system was implemented using Orange tool and five different ML approaches were explored and compared on breast cancer dataset.