Designed and implemented a Linear Regression model to optimize daily operational efficiency by forecasting workforce requirements, streamlining employee scheduling, and enhancing attendance tracking accuracy. Developed a robust Decision Tree algorithm combined with Cosine Similarity-based retrieval methods to ensure fast and reliable access to employee records and operational data, achieving an overall system accuracy of 98.2%. Created an intuitive, user-friendly front-end interface using HTML and CSS, enabling smooth navigation and real-time data management for both administrators and HR personnel. The system showcased practical integration of predictive analytics with frontend design, addressing real-world HR challenges in scheduling, resource planning, and information retrieval.