The document presents a hybrid artificial intelligence model called integrative Random Forest classifier with Genetic Algorithm optimization (RF-GA) to predict risk of delay in construction projects. A literature review found that AI models have been applied to construction project management but few have addressed risk prediction. The study collected data on delay sources from previous projects and experts. It developed the RF-GA model to analyze the data and predict time delays. The RF-GA model was evaluated against performance measures and the classic RF model, demonstrating better accuracy, classification error, and Kappa values of 91.67%, 8.3%, and 87%, respectively. This validated the ability of the hybrid model to handle non-linearity and complexity in construction project data.