Dimensional quality assessment (DQA) of precast laminated panels (PLPs) is required to ensure the installation of the components on the construction site. However, existing methods cannot meet the precision and comprehensiveness of PLP’s DQA. In this paper, we propose an automated multi-dimensional quality assessment method for PLPs based on point cloud data (PCD). After pre-processing the original PCD, the scanned PLPs’ PCD is automatically extracted by the machine learning algorithms, and down-mapped in different directions to generate two-dimensional (2D) images. DQA of PLPs can be realized automatically by the image feature detection algorithms. The validation experiment is conducted on three PLPs. The result shows that the proposed method meets the dimensional quality assessment accuracy of precast laminated panels.