Additive manufacturing (AM) technologies, particularly laser powder-bed fusion (LPBF), are critical in producing lightweight metal components for industries like aerospace and automotive. Development of techniques that make the qualification process of AM parts more efficient and accurate are highly desirable, e.g., witness specimens incorporating complex geometries permit quality assessments early in the process. To predict the behavior of AM parts accurately requires high-fidelity material characterization laboratory tests and the use of these test data to build accurate material models. This paper shows how a framework for the phenomenological modeling of AM materials, i.e., modeling directly based on measured data from mechanical experiments without considering micromechanical effects, has been implemented in LS-DYNA’s MAT_213 material model for use with AM structural components. Present investigations focus on AM aluminum alloys Al2139 and AlSi10Mg featuring characteristics of the mechanical behavior that are challenging for simulation. To predict those characteristics, anisotropic elastoplastic properties were obtained through macro-mechanical experimental tests. Test results were fed into MAT_213 material model to predict the mechanical behavior of the material by finite element (FE) simulations. Two validation examples show how detailed tabulated input in MAT_213 can be used – results show low prediction errors for the overall specimen behavior with errors as low as 0.6% for Al2139 and 0.9% for AlSi10Mg, while stiffness values were predicted with errors less than 10%. The framework can be easily extended to create simulation models for more sophisticated geometries and other AM manufacturing techniques where there is evidence of orthotropic viscoelastic-plastic material behavior.