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Coronary illness is one of the significant reason of death in the world today. An early detection and accurate prediction of the heart disease is needed so as to reduce the mortality rate. Prediction of Heart disease is very challenging, it is even difficult task for medical practitioners as it demands expertise and higher knowledge. Recent development in medical supportive technologies based on machine learning plays an important role in predicting cardiovascular diseases. Machine learning uses algorithms to analyse data, learn from that data and make well-informed learning based decisions. The present paper proposed a new hybrid model based on feature selection, feature optimization and ensemble technique. This exclusive combination will build an enhanced model that will have leverage over the existing models in predicting the heart disease more quickly and accurately and thus will assist the medical practitioners in taking the measures to control the mishap.