In this paper, we have focused on the survival analysis of heart failure patients. The number of individuals diagnosed with coronary failure is increasing and projected to rise by 46 percent by 2030, leading to quite 8 million people with coronary failure. The reason for the increase in heart failure is due to an increase in the number of cases involving high blood pressure, valve disease, thyroid disease, kidney disease, and diabetes [1]. With the growth of machine learning, data mining, statistical analysis, data-modeling predicting whether the person will survive [2] or not after heart failure is possible and it becomes very crucial.