Abstract The Lost and Found Portal is a smart, web-driven system developed to streamline the process of reporting, tracking, and reclaiming misplaced items within institutional settings. It combines HTML, CSS, PHP, and MySQL technologies with AI-based image recognition and analytical tools to enhance recovery performance. Experimental outcomes indicated a 72% improvement in retrieval success compared to traditional manual procedures, achieving 98.7% accuracy in user authentication and 91% in image-based item identification. The system reduced average user response time by 55% and lowered administrative effort by 43% through workflow automation. The research confirms excellent scalability, strong data consistency, and high user satisfaction. Stress testing under simulated concurrent usage displayed stable throughput with minimal data loss. Feedback from users yielded a System Usability Scale (SUS) score of 92.3%. The proposed approach advances institutional digital modernization through a secure and adaptable information management system. It further applies predictive analytics to detect lost-item trends and employs a blockchain-backed claim log, enhancing transparency, preventing tampering, and enabling real-time recovery insights. Keywords: Web-Based System, Lost and Found Portal, Intelligent Retrieval, Secure Authentication, Artificial Intelligence, Institutional Management System.