This study presents the development of an advanced analytical model for the determination of cyclist throw distance in a collision with a motor vehicle. The model considers three key input parameters: the vehicle’s speed, the cyclist’s mass, and the cyclist’s initial speed. A second-degree polynomial regression in three variables was applied, resulting in two functions: one for calculating the throw distance and an inverse function for estimating the vehicle speed. The models were validated using 810 real collision scenarios, demonstrating over 99% accuracy (R2 > 0.997) and a mean error below 0.5 units. Additionally, statistical analyses were conducted, including t-tests and standardized beta coefficient calculations, to determine the impact of each input parameter on the output variable. The results indicate that vehicle speed is the most influential factor, while the cyclist’s mass and speed have minimal effect.