The 7075-T7451 aluminum alloy, widely used in aerospace, aviation, and automotive fields for critical load-bearing components due to its excellent mechanical properties, suffers from residual stresses induced by thermo-mechanical coupling during milling, which deteriorate workpiece performance. This study explores how key milling parameters-spindle speed *n(c)*, feed per tooth *f(z)*, cutting depth *a(p)*, and cutting width *a(e)*-affect surface residual stress and cutting force via orthogonal experiments and finite element analysis (FEA). Results show *a(e)* is critical for X-direction residual stresses, while *f(z)* dominates Y-direction ones. Cutting force increases with *f(z)*, *a(p)*, and *a(e)* but decreases with higher *n(c)*. Multivariate regression-based prediction models for residual stress and cutting force were established, which effectively characterize parameter-response relationships with maximum prediction errors of 18.69% (residual stress) and 12.27% (cutting force), showing good engineering applicability. The findings provide theoretical and experimental foundations for multi-parameter optimization in aluminum alloy milling and residual stress/cutting force control, with satisfactory practical effectiveness.