The health risk prediction and prevention platform uses data analytics, machine learning (ML), and artificial intelligence (AI) to predict potential health risks and recommended preventive measures. These platforms integrate a wide range of data, including electronic health records (EHRs), genetic data, lifestyle data, and real-time user data to provide personalized risk assessments. They can help people and doctors reduce risk and improve health management by detecting early warning signs and making appropriate recommendations. The stage is planned to progress preventive care and make steps quiet results. In the healthcare sector, the proposed prediction and prevention techniques have been found useful in many real-world situations where customization is required for the smooth functioning of the technology. Also, to make life easier and healthier, the presence of such a field is necessary in the current research scenario. Various existing algorithms in the field of healthcare domain are also listed in the paper for further clarification.