To generate a series of physiologically plausible cervix CTVs by biomechanically modeling organ deformation as a consequence of bladder filling. This series can serve as planning CTVs for radiotherapy treatment of cervical cancer patients using a library of plans (LoP) strategy. Methods: The model was constructed based on the full and empty bladder scans of 20 cervical cancer patients, for which the bladder, rectum and the clinical target volume (CTV) of the cervix were delineated. Finite element modeling (FEM) was used to deform empty to full bladder anatomy. This deformation comprised two steps. In the first step, the surfaces of the bladder and rectum of the empty bladder anatomy were explicitly deformed to the full bladder anatomy and imported as enforced displacements into the biomechanical model. These surface displacements cause volumetric deformations of the bladder, rectum and cervix CTV meshes, dictated by their respective elastic properties and the type of contact among them. In the second step, the residual offset between the simulated and target CTV was corrected by an additional thin plate spline warp. Intermediate structural outputs of a linear superposition of the biomechanical and residual warp then constituted the library of CTVs for each patient. The residual warp was minimized by optimizing the FEM parameters over the 20 patients. Finally, the model was tested for nine healthy volunteers for which repeat MR scans were available as the bladder filled from empty to full. Small and large movers were identified depending on the extent of CTV motion, and analyzed separately. The proposed method was compared against the method currently used in our institute, in which intermediate structures are linearly interpolated between full and empty bladder anatomy, using a thin plate spline warp. The comparison metrics used were the ability to preserve CTV volume throughout the deformation, and residual offsets between repeat and library CTV. Results: Optimal model parameters were found to be compatible with published values. While for the current method, the median CTV volume shrunk by 4% for large movers halfway the deformation (and by up to 10% for individual cases), the proposed FEM-based method preserved CTV volumes throughout the deformation. Regional residual errors between repeat and library CTV reduced by up to 3 mm when averaged over the group of large movers. For individual cases this regional error reduction could be as large as 8 mm. Conclusions: We developed a robust and automatic method to create a patient-specific FEM-based LoP. The FEM-based method resulted in more accurate library of planning CTVs as compared to the current method, with the greatest improvements observed for patients with large CTV motion. The biomechanical model simulates volumetric deformations from empty to full bladder anatomy, paving the way for dose accumulation in an LoP setting.