The intricate tendon system of the human muscular-skeletal system contributes to the human hand’s dexterity. A complex bond graph model of the index finger was developed to give insight into this system. Previous validation of this model by use of the ACT hand was difficult due to static joint friction. A new robotic testbed, Utah’s Anatomically-correct Robotic Testbed (UART) finger, has been developed to mitigate this friction. Static force and position experiments were conducted with the UART finger in contact with a surface and were compared to the bond graph model. The results suggest that the model is capable of simultaneously predicting static poses and fingertip force. The average predicted joint angle error was 2.9°. The average fingertip force magnitude error was 7.4%, and the average fingertip force direction error was 4.3°.