Abstract: Three-dimensional geological modeling (3DGM) in mining offers an intuitive representation of underground geological structures. This visualization significantly enhances the precision and efficiency of mining operations. Additionally, it helps to reduce risks and optimize resource utilization. This paper summarizes the principles and methods of existing 3DGM technologies. It reviews the current application status of 3DGM in mining development. Furthermore, it discusses the challenges faced by current 3DGM technologies and their future development trends. 3DGM is to use computer 3D graphics technology to integrate scattered exploration data into a digital model reflecting geological structure and property changes. These models can be divided into surface model, volume model and mixed model. According to the purpose and data source, it can also be subdivided into static model (structural model, stratigraphic model, attribute model) and dynamic model. The modeling process includes data acquisition, processing and model construction. It involves diverse data sources such as geological exploration data, remote sensing data and engineering data. A variety of interpolation methods are used to make up for the data deficiency. Various modeling software has been developed both domestically and internationally. In mining applications, 3DGM is primarily used in mineral resource development, mine design, and safety management. By building accurate 3D models, it improves the understanding of underground structures and enables intelligent resource estimation and dynamic management. 3D ventilation simulation and visualization technologies optimize ventilation systems and reduce costs. Furthermore, integrating 3DGM with automated equipment and sensor technologies facilitates real-time monitoring, precise positioning, and dynamic adjustments in mines. In mine disaster monitoring, 3DGM enables the graded assessment of mining hazards. Combined with numerical simulation techniques, it provides effective support for disaster prevention and risk mitigation, ensuring the safety of personnel. However, current 3DGM technologies face challenges such as low data processing efficiency and insufficient automation. Future developments should integrate artificial intelligence to advance 3DGM towards greater intelligence and automation.