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Abstract Li‐ion batteries are attracting an increasing attention due to the process of electrification involving different industrial sectors. Many efforts are dedicated to improving battery performance in terms of cyclability, capacity, fast charging and safety to name a few. Therefore, it is of primal importance to identify and understand the degradation modes that stay behind cell failure. In this sense, Loss of Lithium Inventory (LLI) and Loss of Active Material (LAM) are considered fundamental indicators for estimating the state of health of a cell. In this work, we introduce an automated open tool which is able to return LLI, LAM and voltage drop due to and eventual development of an internal resistance by fitting experimental pseudo‐OCV profiles of a cell, at its beginning and end of life, with a simulated curve obtained from the pseudo‐OCP curves of positive and negative electrodes. The tool is based on a mathematical model consisting in linear transformations that keeps it simple and guarantees for low computational cost. The model is validated against bibliographic dataset and tested on experimental curves from lab‐scale coin and commercial cylindrical cell with different chemistries.