Excessive and unpredictable temperature rise in electrical machines can not only damage the motor over time but also induce errors in the control of the complex machinery and systems in which they are integrated. Traditionally, temperature reduction in electrical machines has been addressed through various optimization methods focusing on the geometric modification of different components independently. This study proposes and evaluates an alternative strategy by selecting material combinations using a multi-criteria decision-making (MCDM) tool known as the VIKOR method. The effectiveness of this method in proposing new materials to reduce temperature is verified using a validated LPTN thermal model developed for a small, brushed DC machine. In a copper losses test simulation with a 5A current injection, the winding temperature was reduced by 20°C by adopting the second material combination. This combination employs a ferrite magnet, Al 356-T6 for the casing, chrome steel for the bearing, metal graphite for the brush, and nylon for the slot winding paper insulation.