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The heart disease is among the foremost problems faced by people around the globe. It is impossible for medical practioners to analyze this data without computation technology. Hence, there exists constant requirement to appropriately discover factors which can effectively and efficiently handle large scale data for future medical diagnosis. Adhering to needs of the healthcare practioners data mining technology is widely utilized as predictive analytics to discover unknown, hidden and useful information from complex and large scale databases. This paper intends to study varied classification techniques which can be utilized for prediction of heart related problems. In, proposed work the focus is to discover an appropriate technique which can assist and benefit future decision making.