<p>Accurate estimation of the electrical parameters of a three-phase induction motor is important for modeling and controller tuning. Among the approaches available for that purpose, the use of data provided by manufacturers is a practical and accessible option. However, in the case of availability of multiple output data, an analysis that determines the most relevant outputs becomes necessary. This manuscript proposes a sensitivity analysis for the selection of the best model output for the parameter estimation of induction motors. Based on the selection, two metaheuristic methods, namely particle swarm optimization (PSO) and differential evolution optimization (DEO), are employed to estimate the parameters from data provided by the manufacturer of motors for the W22 IR3 Premium model for different sets of outputs. The results show parameters estimated from the most relevant outputs yield improved accuracy compared to those derived from conventional no-load and locked-rotor test methods.</p>