Abstract: With the increasingly prominent strategic status of phosphorus resources, safe, efficient, and green mining of gently inclined phosphate ore bodies has become a key technology for ensuring national resource security and promoting the sustainable development of the chemical industry. This paper systematically reviews the research progress on efficient mining technology for gently inclined phosphate ore bodies and looks forward to their future development directions. Focusing on the geological and mining technical challenges of gently inclined phosphate ore bodies, such as significant variations in ore body thickness, interlayered weak muddy strata, and poor roof stability, this paper highlights the adaptability of mining methods, key technical issues, and path optimization. The pre-controlled roof mechanized layered advancing room-and-pillar method, segmented room-and-pillar method, and their optimized variants exhibit significant advantages in roof stability control, ore recovery rate improvement, and dilution rate reduction. Filling mining technologies, including waste rock cementation filling, upward horizontal layered filling, and strike strip filling, effectively control ground pressure, waste disposal, and reduce surface disturbance, embodying the concept of green mining. Innovative technologies such as trackless mechanization and non-explosive continuous mining promote the development of mining operations towards intelligence and automation. With intelligent hole arrangement, remote control, and mechanized cutting, mining efficiency and safety have been significantly improved. However, mining gently inclined phosphate ore bodies still faces key technical challenges such as large spatial variability of rock mechanical properties, difficulties in quantitative evaluation of goaf stability, and the coordinated optimization of economic and environmental benefits of mining methods. Future research directions should focus on: deepening the study of deep rock mechanical behavior under complex conditions; developing dynamic quantitative evaluation methods for goaf instability risk based on multi-source data fusion and numerical simulation; constructing multi-objective mining method optimization models that integrate technical, economic, environmental, and social benefits; and accelerating the construction of intelligent mines centered around big data, the Internet of Things, and intelligent equipment.