The success of lumbar interbody fusion, the key surgical procedure for treating different pathologies of the lumbar spine, is highly dependent on determining the patient-specific lumbar lordosis (LL) and restoring sagittal balance. This study aimed to (1) develop a personalized finite element (FE) model that automatically updates spinal geometry for different patients; and (2) apply this technique to study the influence of LL on post-fusion spinal biomechanics. Using an X-Ray image-based algorithm, the geometry of the lumbar spine (L1-S1) was updated using independent parameters. Ten subject-specific nonlinear osteoligamentous FE models were developed based on pre-operative images of fusion surgery candidate patients. Post-operative FE models of the same patients were consequently created. Comparison of the obtained results from FE models with pre- and post-operation functional images demonstrated the potential value of this technique in clinical applications. A parametric study of the effect of LL was conducted for cases with zero LL angle, positive LL angles (+6° and +12°) and negative LL angles (−3° and −6°) on fused level (L4-L5), resulting in a total of 50 fusion simulation models. The average range of motion, intradiscal pressure, and fiber strain at adjacent levels were significantly higher with decreased LL during different directions except axial rotation. This study demonstrates that the LL alters both the intersegmental motion and load-sharing in fusion, which may influence the initiation and rate of adjacent level degeneration. This personalized FE platform provides a practical, clinically applicable approach for the analyses of the biomechanical changes associated with lumbar spine fusion.