Circuit Breaker (CB) is one of the most critical assets in our transmission and distribution network. Any failure of CB will result in severe supply interruption to the customers. So far, unless it is switched out for inspection and maintenance, there isn’t an all in one, robust and practical method to monitor the condition of CB continuously and identify the CB with incipient defect. Our project focuses on designing a tailored-made solution for Online Circuit Breaker Monitoring System (OCBMS) for a fleet of over one thousand CBs by monitoring the current profile of the trip coil of CBs. Through a statistical model and machine learning approach, circuit breakers with abnormal performance can be spot out and preventive action can be made immediately before the breakdown of those circuit breakers. The reliability of our distribution network can significantly be improved through our cost effective design.