Japan’s internal migration and foreign population inflows have exhibited strong regional disparities, with urban prefectures continuing to attract disproportionate shares of new residents. This study investigates the spatial diffusion patterns of foreign populations across Japan’s 47 prefectures from 2020 to 2025 using official migration statistics and GIS-based prefectural boundary data. Tokyo recorded the highest foreign inflow (47,384 persons in 2023), followed by Kanagawa (25,286) and Saitama (29,020), while Chiba (−11,590) and Aichi (−4,765) exhibited substantial net outflows. Although diffusion-based models traditionally assume continuous local movement across adjacent regions, foreign migration in Japan often involves selective, policy-driven, and non-adjacent flows. To address this, the study extends the Laplacian diffusion framework by integrating gravity-based spatial terms that account for long-distance attraction effects. Each prefecture was represented as a node within an adjacency matrix derived from polygon neighbor analysis, and migration potential was estimated as a function of inter-prefectural connectivity and population differentials. Preliminary Laplacian coefficients indicate high diffusion intensity within the Tokyo–Kanagawa–Saitama cluster and low gradient values in peripheral prefectures such as Akita, Tottori, and Kochi, reflecting weak inflow attraction. The hybrid Laplacian–gravity model improved the predictive accuracy of migration patterns and revealed that regions with strong labor demand and foreigner integration programs act as key population attractors. The findings highlight spatial inequities in foreign migration diffusion and underscore the potential of targeted migration policies to facilitate the redistribution of foreign residents toward rural prefectures. This research provides empirical evidence that managed foreign migration can contribute to Japan’s regional revitalization and sustainable demographic balance.