Modeling the human finger tendon system becomes difficult when the finger contacts the environment. A bond graph model was developed to intuitively model the interconnected tendon system of the human finger and was validated with human-like robotic fingers. Previous validation of this model has focused on static fingertip forces or static finger position given tendon tensions or positions. This work seeks to expand validation experiments by conducting dynamic simulations of finger motion and fingertip forces simultaneously. To conduct dynamic validation, parameters of the bond graph model need to be calibrated for dynamic motion. Using Utah’s Anatomically-correct Robotic Testbed (UART) finger, model parameters were estimated using experimental methods. By using these new estimated parameters, the bond graph model can now accurately simulate quasi-static motion and fingertip forces of the UART finger while in contact with a surface.