The value of measurement age, blood pressure, weight, smoking habits, exercise, and blood serum cholesterol in predicting death and coronary cardiopathy was studied over an amount of ten years. Sixteen teams comprising 12 763 men aged 40-59 years (at the outset) from 7 countries (Yugoslavia, Finland, Italy, Kingdom of The Netherlands, Greece, USA, and Japan) were studied. the very best risk factors were found to be age, pulse blood pressure, and blood serum cholesterol concentration (related to saturated fatty acids within the diet). Variations in incidence rates couldn't be shown to be associated with characteristics of the cohorts in relative weight, smoking habits or physical activity. To design a perceptive model for heart illnesses acknowledgment using data mining strategies that are fit for enhancing the constancy of heart infections conclusion. Thereafter, we divide this data into Training and Testing Data Sets and employ Naïve Bayes technique to obtain relatively higher prediction accuracy. The primary goal of this research would be given a highly accurate prediction of Heart Disease. As we have done a combination of Genetic and Naïve Bayes Technique, the Investigation would be developed a Hybrid model of both these techniques and called it Hybrid Genetic Naïve Bayes Model for predicting high accuracy in results.