Material extrusion (MEX) is an additive manufacturing process to fabricate prototypes using thermoplastic polymers. As this additive manufacturing technology continues to mature from a rapid prototyping process to a rapid manufacturing technique, predicting the mechanical behavior of 3D printed parts using representative models becomes essential for translating products quickly from bench to market. Predictive models allow product designers to accurately forecast mechanical performance while reducing the overall design cycle and reliance on costly physical experimentations. This research presents an integrated approach at the process-property- performance nexus to characterizing process-induced properties and effectively utilizing the measured properties within a predictive analysis framework tailored to design MEX-printed products. To this end, two methods were investigated leveraging the anisotropy of additively manufactured parts. The first method involved using finite element simulations to separate the part into bonded layers corresponding to 3D printed layers and individually applying the raster angles to each layer. The second method employed the classical lamination theory, ubiquitous in the analysis of laminated composite materials, to calculate effective, homogenized properties based on the number and orientation of the layers. Using individual cells in finite element software to represent layers and averaging layer properties has proven effective in modeling MEX parts for stress analysis. Case studies using MEX-printed ULTEM 9085 structures are presented to verify the effectiveness of developed models. The results provide a practical design pathway to shorten the development cycle and accelerate the deployment of additively manufactured parts in load-bearing scenarios.