This study presents a computational mechanics framework to model processing-induced strengthening in a bio-based semi-crystalline polymer, poly (L-lactic acid) (PLLA). When a molded PLLA specimen is subjected to tensile pre-processing, molecular orientation and strain-induced crystallization occur, resulting in increased stiffness and strength under subsequent tensile loading in the same direction. Although this phenomenon is well recognized experimentally, a quantitative numerical description linking the local deformation history during processing to post-processing mechanical properties remains limited. In the present work, the tensile pre-processing stage is simulated using a particle-based method, Smoothed Particle Hydrodynamics (SPH), which is well suited for large deformation, free-surface motion, and strongly non-uniform strain fields. Instead of using individual shear components, which are direction-dependent in three-dimensional deformation, the second invariant of the strain tensor is introduced as a rotationally invariant scalar measure of deformation intensity. The cumulative history of this invariant obtained from the SPH simulation is assumed to govern strain-induced crystallization. Local stiffness and tensile strength are then assigned as functions of the accumulated invariant. Subsequently, the tensile deformation and failure behavior of the pre-processed specimen are analyzed using the finite element method. Model parameters are identified by comparing simulated and experimental stress–strain responses before and after pre-tensile processing. The proposed framework successfully reproduces the experimentally observed enhancement in stiffness and strength. The results demonstrate that the second strain invariant provides a physically consistent and direction-independent descriptor for linking large-deformation processing simulations to constitutive property evolution. This approach offers a general computational strategy for modeling deformation-induced property changes in semi-crystalline polymers under complex processing conditions.