Abstract: Nanoporous metals are a type of metallic material that contain a large number of nanoscale pores. These materials are characterized by their outstanding surface effects and exhibit superior mechanical properties compared to traditional porous metals. Compared with theoretical and molecular dynamics simulations, finite element methods are more suitable for complex structural models. However, limited by theoretical difficulties, previous research has often simplified the models of nanoporous metals into relatively simple two-dimensional structures, which cannot provide an accurate depiction of their mechanical properties. Therefore, this study employs the principle of minimum energy and the surface theory of nano-materials to develop a finite element surface element that considers the surface effect of nanoporous materials. By considering the non-uniformity of the microscopic structure, we further develop a finite element computational model that enables the analysis of the mechanical behavior of three-dimensional nanoporous metal materials. We verify the effectiveness of our developed finite element model by comparing the calculated stress distribution near the nano-pores with the reference literature. Using the developed computational model, we perform single-axis tension and compression simulations on nanoporous metal materials containing either single spherical pores or random multiple spherical pores, and investigate the influence of porosity, pore quantity, and surface parameters on the Young's modulus, yield strength, and energy absorption capacity of nanoporous metals. Our results demonstrate that the developed finite element model can accurately capture the stress distribution near the nano-pores. Furthermore, our findings indicate that the Young's modulus of nanoporous metals significantly depends on the residual stress on the pore surface and the loading direction, rather than the surface Lamé constant. In summary, the developed finite element model provides a scientific evidence for the mechanical performance prediction of nanoporous metals.