The amount and variety of medical devices are tremendous, and the management of medical devices has been taken on a new level of complexity due to the increased sophistication and specialization of equipment. An Equipment Maintenance Model using Artificial Intelligence is developed to analyze information from internal databases, the manufacturer and the particular equipment. A tablet is provided to technicians to access the model for analysis results through a web-base user interface while they are maintaining the equipment on site. Information such as equipment condition, possible root causes and recommended follow up actions can be obtained. Managers can also monitor equipment maintenance status, such as the spare parts stock level, equipment condition and predicted maintenance schedule with the model. The three main features are described as follow: i. Smart Spare Parts Management – Optimal stock level of each spare parts is deduced and users will be reminded to place order accordingly. ii. Smart Troubleshooting – With reference to the input parameters and the database, the model would suggest the possible root causes for troubleshooting. iii. Smart Predictive Maintenance Schedule – Equipment health, quantify as healthscore, would be evaluated. The time of the next possible fault and thus the maintenance schedule are predicted.