The formation of liver fibrosis patterns is a complex dynamic and multi-cellular process that can only be marginally investigated experimentally. A digital liver twin model is warranted, as it permits integration of multiple mechanisms and study of consequences upon their modulation. We developed a computational liver model on chronic injurymediated formation of septal fibrosis that is based on experimental iteration. This liver "digital twin" (DT) constitutes a "model" of the reality, closely reproducing the spatial-temporal pattern of hepatocytes, hepatic stellate cells (HSC), macrophages (Mph) and collagen fibers through literature and quantitative imaging of mouse experiments. The DT represents liver tissue microarchitecture containing ECM networks, hepatocytes, blood vessels, non-parenchymal cells, and cell-cell communication. The DT can precisely simulate formation of septal fibrosis and predicts that attraction of activated hepatic stellate cells (HSC) and macrophages (Mph) is controlled by spatial-temporal damage associated molecular patterns (DAMPs) released from CYP2E1 expressing hepatocytes due to CCl4-induced injury. In addition, undamaged hepatocytes proliferate to replace the dead ones, thereby mechanically compressing the fibrotic collagen network into "wall"-like shapes. The DT is validated by perturbations, like lacking hepatocyte proliferation, HSC migration or Mph phagocytosis. Importantly, simulations assuming loss of CYP2E1 match experimental data from mice with deleted transcription factor GATA4 in endothelial cells that present with decreased CYP2E1 expression and disturbed distribution pattern in hepatocytes. Simulations and biology both show diffuse perisinusoidal instead of bridging fibrosis. In conclusion, we have generated a DT that can simulate septal fibrosis formation upon liver damage.