<p>Milling force is an essential parameter for evaluating the milling process. To control the milling process of graphene-reinforced aluminum matrix composites (GRAMCs) better based on milling force, a milling force prediction method is proposed in this study, which combines finite element and regression analysis. First, the cutting edge of the milling cutter is discretized into cutting micro-elements along the axial direction, which is based on the results of the geometric analysis. The milling process can be considered a series of orthogonal cutting processes of cutting micro-elements by the equivalent plane method. Subsequently, a GRAMCs model that accounts for the random distribution of graphene positions and orientations was developed, and it is used to facilitate the finite element simulation of the cutting process of multiple sets of micro-elements with varying cutting speeds and undeformed chip thicknesses. The impact of undeformed chip thicknesses and cutting speeds on the cutting forces was then investigated. Ultimately, the unit cutting force was mechanically modeled by regression analysis and fitting the cutting simulation results, to obtain the unit cutting force considering the cutting speed. The milling force prediction was then achieved through vector integral summation. A comparison and analysis of the milling experiments revealed an average error of 8.12% in the prediction of milling force along the X-axis, and an average error of 4.84% along the Y-axis. The method of micro-elementary cutting simulation and milling force prediction presented in this study is reliable and accurate, and the results provide a foundation for further research on the machining performance of GRAMCs.</p>