Accurate reconstruction of vehicle collisions is essential for understanding incident dynamics and informing safety improvements. Traditionally, vehicle speed from dashcam footage has been approximated by estimating the time duration and distance traveled as the vehicle passes between reference objects. This method limits the resolution of the speed profile to an average speed over given intervals and reduces the ability to determine moments of acceleration or deceleration. A more detailed speed profile can be calculated by solving for the vehicle’s position in each video frame; however, this method is time-consuming and can introduce spatial and temporal error and is often constrained by the availability of external trackable features in the surrounding environment. Motion tracking software, widely used in the visual effects industry to track camera positions, has been adopted by some collision reconstructionists for determining vehicle speed from video. This study examines the accuracy and reliability of using one such 3D tracking software, SynthEyes, for this purpose. Dashcam footage of a VBOX-equipped test vehicle, in a 3D laser scanned environment, was processed using SynthEyes to track the camera and calculate vehicle speed based on an understanding of the dashcam’s average frame rate. The resulting speed profiles were analyzed and compared to the VBOX’s high-accuracy GPS data. Data processing methods were explored and evaluated to determine which, if any, filtering techniques reduced variability and best approximated the actual speed profile of the vehicle. The findings indicate that SynthEyes provides a viable solution for speed estimation in collision reconstruction across a wide range of vehicle motion, with potential errors minimized through use of a standardized workflow, importing 3D scene data, and appropriate data filtering. The software can be a valuable tool for accident reconstruction investigators.