This paper proposes a study on plane feature extraction in registration of multiple laser scanning data sets for reverse engineering (RE). The objective of this proposed method is to solve 3D registration problem with different form and distribution data sets, to acquire an accurate 3D CAD model so that the purpose of reverse parts accurately can be obtained, and to speed up the computation time. The registration process is carried out in two steps: rough registration and continued by fine registration which is combined with plane features extraction. Firstly, two or more point cloud data sets yielded from different scanning position are registered roughly by using transformation process (rotation and translation) to obtain the best initial position. Secondly, grid reconstruction of pairwise data sets and grid data pattern identification are applied. Thirdly, plane features of pairwise grids are extracted and validated by using some certain criteria. The aim of the validation is to convince only validated plane data involved in the fine registration process Finally, the fine registration of pairwise data sets is conducted by using the selected validated plane data. In this fine registration, iterative closest point (ICP) process is applied based on both point-to-point and plane-to-plane with brute-Force and kD-tree scenarios. Root mean square (RMS) of pairwise point distance and computation time are obtained over the iteration process for all scenarios. To check the behaviour of validation process in fine registration, computation in each validation steps is also performed. The experiment result shows the extraction and validation planes improved the precision in both point-to-point and plane-to-plane registration in entire scenarios while kD-tree yields faster convergence. The benefits of the proposed method compared with existing methods are simpler and user-friendly, more applicable for RE of many manufacturing products, more accurate 3D CAD model result and shorter computation time.