<p>Globally, the impact of cardiovascular diseases (CVD) has been increasing day by day. As we all know, there are various factors influencing CVD, particularly heart-related diseases. But, due to the present condition of the environment, human lifestyle, food habits, and working environments, it is unlikely to predict the cause of the heart diseases. Even a person who is considered to be healthy with all the parameters like cholesterol, height, weight, Body Mass Index (BMI) and so on, may face heart-related issues suddenly. Hence, even though there is a lot of research that has been undergoing related to this study, the aspect of the problem, prediction, number and kinds of features, and the techniques adopted vary from research to research. This variation is due to the number of features and the effect of those features considered for one person may have conflict with another person. Considering the liveliness of the research, in the present paper, we have analysed the risk factor prediction by Structural Equation Modelling (SEM), and Artificial Neural Networks (ANN). The structural equation modelling is used to find the relationship between variables and artificial neural network is used for risk prediction in which the average mean square error (MSE) for the proposed ANN model is 0.2040.</p>