This paper proposes a design procedure based on multi-objective optimization for modeling a Peltier thermoelectric system using experimental data. A multi-objective evolutionary algorithm was used to identify a set of optimal parameters that satisfactorily characterize the system’s dynamics. The proposed methodology offers a designer valuable information about the dynamics of the temperatures of the Peltier’s hot and cold surfaces and the trade-offs between their design objectives (visualized in the Pareto fronts). In this way, a control engineer can be sufficiently informed to choose, according to their preferences, a model for the Peltier cell with the best performance (for different system operation scenarios). A Peltier cold-side temperature model was selected to tune a proportional-integral-derivative (PID) controller and evaluate the robustness of the model. The tuned PID controller works directly on the nonlinear model of the Peltier cell, allowing it to effectively control the temperature of the cold surface of the thermoelectric module. The methodology uses the Integral Absolute Error (IAE) as a performance index to evaluate the quality of system modeling. The results show that the methodological approach applied to model and control the system performs very satisfactorily.