The use of advanced medical equipment in hospitals necessitates effective maintenance policies that would ensure reliability, the health of the patients, and cost-effectiveness. Traditional reactive or planned maintenance will barely assist in preventing unexpected equipment failure. Predictive maintenance can be employed with the help of AI and ML, study sensor data, historical logs, and usage trends to detect signs of degradation early enough, calculate the remaining useful operation period, and automatically schedule the maintenance process. This would be used to prevent the sudden failure and wastage of resources and extend the life of the important equipment, such as MRI machines, ventilators, and infusion pumps, among others. Despite the limitations with interoperability and regulatory compliance, AI-based maintenance has been growing in transforming the healthcare infrastructure by enhancing operational resilience and patient care.