This article presents an uncertainty analysis of several of the most commonly used methods for calculating motor vehicle collision speeds. Based on a real-world crash test, a simulation-based collision model and an energy-based post-impact vehicle motion were developed in MATLAB. The calculation results were optimized using the Monte Carlo method. A custom-designed script was employed to search the full range of feasible solutions, and the results were compared with those obtained from analytical reconstruction methods and simulations conducted in two commercially available vehicle dynamics software packages. The study demonstrated that analytical calculations are highly sensitive to uncertainties in estimating the base post-impact trajectory angles and, depending on the reconstruction type (I, II, III, IV), to pre-impact approach angles. This sensitivity is not observed in simulation-based calculations, regardless of whether the post-impact motion is modeled using energy methods or vehicle dynamics models integrated into accident reconstruction software. Additionally, the performance of optimization algorithms built into these programs was analyzed. In this test, the uncertainties for the different methods – at measured speeds of 42.1 and 30.0 km/h – did not exceed ±13%. In contrast, randomizing the friction coefficient (µ) resulted in uncertainties of up to ±28% and varied across individual vehicles. These values are consistent with the theoretical analyses conducted by other researchers.