Abstract: Computerized systems and methods are provided that utilize a machine learning model to predict anomalies for a radio access network site device and taking corrective action. After a radio access network site device has received a software update, key performance indicators are extracted from the data from the radio access network site device. The key performance indicators are utilized with an anomaly risk model to determine if one or more of the key performance indicators exceeds a baseline threshold for the one or more radio access network devices. Responsive to the one or more key performance indicators exceeding a baseline threshold, a corrective action is initiated modifying the one or more radio access network devices.