There are provided a method and system to control traffic in a cellular network comprising a plurality of access points (APs) serving a plurality of user equipment devices (UEs). The method comprises: using a machine learning (ML) model to classify at least part of the APs in accordance with a first part of AP metrics thereof, thereby giving rise to a plurality of classes, each comprising peering APs; for a given class, processing AP performance metrics of peering APs classified to the given class to identify, among them, one or more first APs with negative performance variations above a variation threshold and, thereby, requiring corrective actions; and enabling one or more corrective actions with regard to the identified one or more first APs.