Accurate hepatic clearance prediction is critical for systemic exposure and DDI assessment, but traditional IVIVE using hepatocyte or microsomal Cl_int shows high variability due to metabolic and structural factors. We developed a modified IVIVE approach based on PBPK simulations that captures liver lobule structure. For CYP3A4 substrates, experimental parameters (fup, fuh, permeability, logP) were converted to model parameters (Vmax, Km) to generate concentration–time profiles, from which PK parameters (Cmax, Tmax, AUC, half-life, CL_sim) were derived. The parallel tube IVIVE model using CLint was compared with CL_sim, and a regression model incorporating a single coefficient D was developed to adjust PT predictions for lobule structure, achieving 95.65% accuracy with low error. These results highlight that integrating PBPK-informed IVIVE with regression-modified PT modeling improves hepatic clearance prediction for translational PK.