The increasing prevalence of non-communicable diseases (NCDs) in Indonesia demands innovation in data-based health risk prediction. This study aims to develop a web-based system that utilizes Monte Carlo simulation to predict health risks based on lifestyle variables and clinical parameters. The system was developed with the Streamlit framework and tested with a simulation approach of thousands of random scenarios using probability distributions. The main features of the system include personal profile settings, real-time health dashboard, and visualization of daily health trends. Risk prediction was performed using the Monte Carlo method, including the likelihood of diabetes, hypertension, heart disease, and obesity. Simulation results show that the system is able to represent physiological data realistically and provide a personalized risk picture that is relevant to the user's condition. This system has the potential to become a preventive tool for the public and medical personnel in increasing awareness and controlling health risks.