As the use of Unmanned Aerial Vehicles (UAVs), especially quadcopters, continues to surge, the performance of lithium-ion batteries becomes increasingly significant. These batteries not only influence the operational autonomy of UAVs but also determine the overall success and longevity of aerial missions. Motivated by the pressing need to accurately evaluate and predict battery behavior over its lifecycle, this thesis starts on the development of a test bench. This bench is specifically designed to develop a predictive model for LiPo batteries, shining a light on their residual charge capacity. The study methodically outlines each step, from the initial design of the test bench to the selection of the right components, and finally, the software implementation.