Abstract: Lithium-ion batteries (LIBs) that reached their end-of-life (EoL) require recycling, rather than disposal, to recirculate valuable metals and protect the environment. This led us to investigate the extraction of metals from the cathodes of EoL lithium-titanate batteries using ethylenediaminetetraacetic acid disodium (EDTA-2Na). In this work, an orthogonal array was used to design experiments and signal-to-noise calculations were used to define the optimal conditions, which were 0.50 mol/L EDTA-2Na, pH 6, 75°C, 180 min, 2% pulp density, and 300 r/min, resulting in 97.96%, 94.79%, 96.45%, and 98.89% leaching efficiencies for Li, Ni, Co, and Mn, respectively. Statistically significant interactions between variables were then identified using Pearson’s correlation at the 95% confidence interval, and the pH and temperature were found to be significant. The extraction efficiency decreased as the pH increased, but increased as the temperature increased. Machine learning fitting using linear regression for multi-output prediction was unsatisfactory, whereas random forest regression (RFR) produced satisfactory results. Permutation importance was computed on the fitted RFR to determine feature importance, and confirmed that the pH and temperature were influential variables; however, the time and pulp density were also noted. As the fitted RFR failed to satisfactorily predict leaching efficiencies in additional validation experiments, we recommend increasing the number of experiments and using additional fitting models. An additional analysis that included the initial oxidation-reduction potential (optimal 33.3 mV) revealed this to be the most important variable, the effect of which largely overshadows those of all the other variables. Finally, an environmental assessment highlighted the benefits of the chelating extraction; however, the economic assessment indicated room for improvement.