Accelerated design for magnetocaloric performance in Mn-Fe-P-Si compounds using machine learning

•An effective method for predicting the magnetocaloric performance of Mn-Fe-P-Si alloys using machine learning is proposed.•Curie temperature, thermal hysteresis, and magnetic entropy change as a function of compositions are clearly displayed.•The composition window suitable for room temperature magnetic refrigeration is optimized to accelerate the alloy design.