Gears are industrial components with a precise geometry. Identification of their basic parameters plays an important role in their reverse design and quality control process. This article describes a new approach for the calculation of helical gear’s basic parameters using optical data acquired by 3D digitizer. This approach is implemented by acquiring cloud-of-points data (COP-data) from the bearing seats and gear tooth surface. Cylinder surface fitting through COP-data acquired from bearing seats is performed for the determination of gear axis of rotation. In a final step, involute helicoid surface fitting through COP-data acquired from gear tooth surface determines the helical gear’s primary features. Particle swarm optimization algorithm as an efficient method is applied to perform the surface fitting process in this article.