The current study aims to determine the influence of machining and production parameters during the milling of Cu/B–CrC composites. The relationship between energy consumption and cutting speed, feed rate and reinforcement ratio were investigated. For this purpose, 2d and 3d graphs for comparison of the effects of input parameters were demonstrated and analyzed. The predictability of the energy consumption during milling was measured by a fuzzy inference system (FIS). According to the graphical and optimization results, the optimum conditions to obtain the minimum energy consumption were 5% reinforcement ratio, 125 m/min cutting speed and 0.2 mm/rev feed rate. A reinforcement ratio of 52.71% was the most effective factor on energy demand followed by the feed rate (24.26%) and cutting speed (12.85%). According to the obtained results, there was a minor margin of error between the actual and predicted findings ranging from 1.6 to 2.4%. Considering the energy consumption is one of the key factors among machinability criteria, the study proposes a comprehensive approach for industrial and academic works.