Injection of charge carriers from the electrodes into the semiconductor layer is a crucial part of the operation in Organic Thin Film Transistors. OTFTs generally suffer from poor charge injection and so gaining an understanding of the contact resistance occurring at the electrode-semiconductor junction is a must. In this work, we test the effect of certain parameters, both physical and electrical, on the contact resistance of the device and design a machine-learning model to reduce the extraction time of the contact resistance and provide faster and easier predictions, given the parameters the contact resistance is being tested for.