The study investigates the mechanical characterization of PET-G components fabricated via Fused Deposition Modeling (FDM), integrating experimental testing with advanced numerical modeling. Initially, an extensive parametric analysis was conducted to determine the optimal printing conditions, focusing on temperature, speed, and infill density to ensure reliable and repeatable sample fabrication. Subsequently, the study employs an inverse problem-solving approach that combines Digital Image Correlation (DIC) with Finite Element Method Updating (FEMU) to identify the material parameters, specifically Young's modulus and Poisson's ratio. The methodology allows for a precise evaluation of mechanical properties by iteratively minimizing discrepancies between experimental strain fields and FEM simulations. The results reveal significant dependencies of material stiffness on infill pattern and density, with Young's modulus varying up to 20% between different configurations. Additionally, the study highlights the limitations of conventional tensile testing for FDM materials, emphasizing the necessity for advanced full-field measurement techniques to account for anisotropy and microstructural heterogeneity. The proposed methodology enhances the accuracy of material characterization, contributing to the development of more reliable predictive models for 3D-printed components. The research provides valuable insights for optimizing FDM process parameters and establishing standardized testing protocols for additively manufactured materials.