Residents of Ratnapura District's communities are seriously at risk from landslides. The creation of precise and timely landslide prediction systems is essential to reduce the risks and improve readiness for disasters. Landslide prediction in the Ratnapura District is the topic of a larger Pre-Disaster and Risk Detection AI Prediction System presented in this paper. The component seeks to offer the likelihood of possible landslides by utilizing cutting-edge machine learning techniques and geographical data. To build a complete landslide prediction model, the suggested system combines topographical and geological data sources. The system examines the correlations between numerous environmental parameters using machine learning methods. The program can produce probabilistic forecasts of landslide occurrences in the Ratnapura District since it has been trained to recognize patterns and trends that precede landslides. The Pre-Disaster and Risk Detection AI Prediction System, which has a dedicated landslide prediction module, makes use of AI and predictive analytics to enhance the Ratnapura District's disaster management approach. This component shows the significance of technology innovation in protecting vulnerable communities from natural disasters as part of a complete risk detection framework.