Heart is the most significant part of human body. In this fast and busy life people eat what they want and diagnosis themselves. As a result they get sick and it results into heart failure. Life is completely dependent on the proper working of heart. If functioning of heart is not properly worked, it will also affect the other body parts of human body such as brain, kidney, etc. Heart Diseases are the major cause of deaths in the world. Various factors that increase the risk of Heart Diseases such as stress, cholesterol, high blood pressure, lack of physical exercise, smoking and obesity etc. The heart disease prediction system helps the physician and healthcare professionals as a tool for heart disease diagnosis. To protect the life of a patient from heart diseases there have to be quick and efficient prediction technique is to be followed. The main goal of this work is to develop an efficient heart disease prediction system using feature extraction and SVM classifier that can be used to predict the occurrence of disease. The prediction of heart disease pattern with classification algorithms is proposed here. Classification is one of the most important tasks in data mining. It is very essential to find the best fit classification algorithm that has greater accuracy on classification in the case of heart disease classification. This cleaned data is classified by the classification algorithms SVM classifier. This technique is widely used to validate the accuracy of medical data.