Abstract
Each disorder is split by heart loss, physical body language, and other abilities that affect an individual's ability to perform everyday activities. Lack of awareness isn't getting to cause these diseases. It's commonest in people 50 years aged and older and younger. The most risk factor is that the sudden shock caused by the amazing things around them. Sleep death is that the second commonest explanation for death for those over the age of 55 that suffer from a stroke. Nowadays, thanks to lifestyle and heredity, health illness is increasing day by day. Especially, heart condition has become quite common lately, meaning people's lives are in danger. Everyone has different values for vital sign, cholesterol and pulse. But consistent with clinically proven results, normal values of vital sign are 120/90, cholesterol 100-129 mg / dL, pulse 72, fasting blood glucose level 100 mg / dL, pulse 60-100 ppm, ECG is normal, the width of the most vessels is 25 mm (1 inch) within the mains and eight μm within the capillaries. this text presents a survey of various classification techniques wont to predict each person's risk level supported age, sex, vital sign , cholesterol, and pulse . The "disease prognosis" system, supported predictive modeling, predicts a user's disease supported the symptoms the user presents as a system input. The system analyzes the symptoms presented by the user as input and provides the probability of the disease as an output. Disease prognosis is performed by implementing 5 techniques like the Nave Base, KNN, Decision Tree, rectilinear regression and Random Forest Mechanisms. These techniques is used for the calculation of the permutations of the disease. Therefore, the typical predictive accuracy probability is 83% obtained.

Key words: Machine Learning, Heart Disease, Naive Bayes, Logistic Regression, Linear Regression, and Random Forest.