Among all types of cancer, one of the most serious types of cancer that causes the unpredictability of mortality in the majority of women across the world is breast cancer (BC). Numerous researches have been done for the BC treatment and also are going on at present at utmost rate which leads to the better understanding of the disease and hence provides better results. Thus accurate prediction of BC plays a vital role in efficient treatment and also for its early stage detection. Since a few years ago, many Machine Learning (ML) algorithms have been suggested for precise BC prediction. In order to improve BC prediction using machine learning analytics, this article also suggests the MLESBCD (Machine Learning Expert System for Breast Cancer Detection). Prior to using the classification algorithm, the MLESBCD the BC data is preprocessed to handle outliers and the missing values. On the BC dataset from the UCI machine learning repository, the suggested MLESBCD generates satisfactory accuracy.