A system for a real time programming of a battery agnostic Battery Management System (BMS) including a processor of a BMS programming server node connected to a controller over a network and configured to host a machine learning (ML) module and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: receive sensory data from a sensor array attached to a battery module having a BMS coupled to the controller; parse the sensory data to derive a plurality of features; query a local BMS database to retrieve local historical BMS data collected from the battery module; generate a feature vector based on the plurality of features and the historical BMS data; and provide the feature vector to the ML module for generating a predictive model configured to output a BMS programming parameter for re-programming of the BMS.