Purpose <p>This study develops a nonlocal bio-heat Moore-Gibson-Thompson (MGT) model for skin tissue that incorporates sweating and nonlocal elasticity within the framework of a memory-dependent derivative. The aim of this study is to achieve more accurate predictions at the microscopic level by accounting both the temporal and spatial nonlocal effects in heat conduction for a skin tissue that incorporates sweating.</p> Methods <p>The obtained partial differential equations are solved by using the Laplace transform technique. To retrieve the solutions in the real-time domain, the Riemann-Sum approximation method is applied for Laplace inversion.</p> Results <p>Numerical simulations are carried out to study the combined effects of sweating, memory effect and nonlocality on the skin tissue. The results are illustrated graphically and compared between the MGT and Lord-Shulman (LS) models to highlight</p> Conclusions <p>The findings reveal that sweating and nonlocal elasticity significantly influence bio-heat transfer in skin tissue. Incorporating memory-dependent and nonlocal effects within the MGT framework yields improved predictions of thermoelastic behavior compared to classical formulations.</p>