A system and method for creating a model for predicting and reducing subscriber churn in a computer network. The method including: for a predetermined time period: retrieving traffic flow data per subscriber for a plurality of subscribers in the computer network; determining at least one metric per subscriber from the traffic flow data; determining at least one systemic feature associated with the plurality of subscribers; and storing the at least one amalgamated metric and feature; on reaching the predetermined time period create the model by: analyzing at least one metric and at least one feature for the predetermined time period; predicting, per subscriber, whether the subscriber is going to churn within a churn period in the future based on the analysis; validating the prediction by determining whether the subscriber actually churned during the churn period; and creating the model based on the validated predictions.