This paper aims to analyze and estimate the factors affecting the State of Health (SoH) of lithium-ion batteries by leveraging advanced evaluation of electrical and chemo-mechanical processes contributing to degradation. The focus was on characterization and collection of empirical battery cycling data investigating the impact of different input variables on SoH prediction to enable predictions for capacity and degradation to validate reliability for second-life applications. The methodology involves collecting cycling data alongside Electrochemical Impedance Spectroscopy (EIS) using a custom test protocol under varied temperatures and charging rates to simulate real-world conditions. The alterations in capacity and the variation of the open circuit voltage with increasing cycles across different temperatures and c rates are also analyzed. The proposed method facilitates a better understanding of the interplay between temperature and C rates on the capacity, open circuit voltage, nominal voltage and EIS response to help estimate the SoH of lithium-ion batteries.