Results from multiple high profile experiments on the parameters influencing the impacts that cause skull fractures to the frontal, temporal, and parietal bones were gathered and analyzed. The location of the impact as a binary function of frontal or lateral strike, the velocity, the striking area of the impactor, and the force needed to cause skull fracture in each experiment were subjected to statistical analysis using the JMP statistical software pack. A novel neural network model predicting skull fracture threshold was developed with a high statistical correlation (R2=0.978" role="presentation">R2=0.978) and presented in this text. Despite variation within individual studies, the equation herein proposes a 3 kN greater resistance to fracture for the frontal bone when compared to the temporoparietal bones. Additionally, impacts with low velocities (<4.1 m/s) were more prone to cause fracture in the lateral regions of the skull when compared to similar velocity frontal impacts. Conversely, higher velocity impacts (>4.1 m/s) showed a greater frontal sensitivity.