Prostate Cancer is the second most regular type of disease in men around the world. Bio-markers have developed as basic devices for treatment and appraisal since the changeability of ailment conduct, the expense and decent variety of medicines, and the related weakness of personal satisfaction have given rise to a requirement for a customized methodology. High throughput innovation stages in proteomics and genomics have quickened the improvement of bio-markers. This project presents an advanced approach towards finding best bio-markers for PC by harnessing the computational power of machine learning.