AI-Enabled Smart Patient Registration System designed to automate and optimize patient on boarding, clinical triage, and health record management in healthcare facilities. The proposed system integrates secure identity authentication, real-time vitals acquisition, and predictive symptom analytics to intelligently recommend appropriate medical departments and generate digital appointment tokens. Machine learning–based symptom classification models analyze patient-reported symptoms and vital parameters to improve triage accuracy and reduce manual intervention. The system is implemented using modern web technologies to ensure scalability, responsiveness, and cross-platform accessibility, while maintaining centralized electronic health records for longitudinal patient data management. Experimental evaluation conducted in a simulated hospital environment demonstrates a reduction in average patient waiting time by approximately 35–45%, improvement in registration data accuracy by over 98%, and department recommendation accuracy exceeding 90%. User feedback indicates enhanced usability and workflow efficiency for both patients and healthcare staff. The results validate the effectiveness of AI-driven automation in improving operational efficiency, clinical decision support, and patient experience, highlighting the system’s potential for deployment in small- to large-scale healthcare institutions.