<p>Aluminum foams have attracted considerable attention from both industry and academia due to their distinctive mechanical and structural properties, which arise from their complex cellular architecture. A thorough understanding of the microstructural transformations during foam production is essential for optimizing such materials’ performance and expanding their industrial applications. In this study, molecular dynamics (MD) simulations employing the angular-dependent potential were performed to extract critical input parameters for developing a phase-field (PF) modeling framework of the aluminum–silicon (Al-Si) system. These parameters include the diffusion coefficient, specific heat capacity, gradient energy coefficient, and grain boundary mobility. The extracted values enable PF models to more accurately predict the microstructural evolution of the Al-Si systems during their foaming process. Alongside MD simulations, a suite of numerical methods including the mean-squared displacement method, energy fluctuation analysis, the capillary fluctuation method, and the random walk method were employed to obtain key thermophysical and kinetic parameters of the Al-Si system, which are difficult to measure experimentally. The established computational framework will ultimately be extended into a multiscale approach to advance the understanding of process–structure–property–performance relationships in metal foams and to enhance the predictive capabilities of multiscale material models for the design and optimization of metal foams.</p>