Abstract: Three-dimensional point cloud data of a steep rock slope was acquired using 3D laser scanning technology. After the filtering preprocessing of the point cloud data, the open-source program Discontinuity Set Extractor (DSE) was then used to semi-automatically recognize and classify the point cloud data, obtaining key parameters and clustering information of the slope rock mass structural planes, such as attitude, trace length, and spacing. By fitting the point cloud clustering information, a probability distribution model was created, and a Discrete Fracture Network (DFN) model was established. Further, a three-dimensional block discrete element model of the steep slope was developed using the "Rhino-Griddle-3DEC" integrated modeling method, based on the point cloud data. The model analyzed the stability of slope and potential failure area. The results show that under the gravity condition, the safety factor of the whole slope is about 1.5 and the potential unstable area is the dangerous rock mass located on the top of the slope. Moreover, the structural plane parameters identified by this method can better reflect the engineering properties of the rock mass, providing important guidance for the analysis and evaluation of the stability of steep rock slopes.