Abstract: To address issues in traditional open-pit mine slope monitoring and early warning, such as limited monitoring technologies, inadequate multi-source data fusion, and ineffective early warnings, this paper reviews the research progress in slope disaster monitoring and early warning from three perspectives: intelligent slope sensing and monitoring, high-precision 3D slope modeling and visualization, and slope stability assessment with risk warning. The monitoring methods, including the Global Navigation Satellite System, the integration of UAV oblique photography with LiDAR, and multi-scale sky-air-ground integrated monitoring, are systematically summarized. Cutting-edge technologies, such as 3D visualization and modeling of complex geological structures, as well as digital twin-driven full-element 3D visualization of slopes, are reviewed. Key technologies, including machine learning-driven intelligent slope analysis, multi-model integrated slope assessment, and intelligent slope monitoring and early warning platforms based on multi-source data fusion, are analyzed and organized. In response to current challenges in open-pit mine slope monitoring and early warning—such as insufficient multi-source information fusion capability, weak interactivity and simulation performance of 3D slope models with poor dynamic visualization, low generalizability of slope risk assessment and early warning models, and a lack of emergency response modules in monitoring platforms—this study outlines development trends for slope disaster safety management: accelerating the establishment of an intelligent sensing and monitoring system integrating multi-source data; enhancing slope risk assessment through digital intelligence to improve the accuracy of machine learning and enable real-time transparent analysis and feedback of slope information; and developing an intelligent disaster monitoring and early warning platform with holistic sensing, collaborative warning, and smart emergency response capabilities.