Abstract: China is the country with the most severe gas disasters. A large amount of in-depth research has been carried out in the early warning of coal and gas outburst disasters and their composite dynamic disasters, and significant results have been achieved. However, in recent years, coal and gas outburst and composite dynamic disasters have still occurred from time to time, and the trend of multi disaster coupling in deep mining mines is becoming increasingly evident. In order to further improve the effective and precise prevention and control of dynamic disasters such as gas and rock burst in deep and high-strength mining mines, enhance the level of mine intelligence, and ensure the safe and efficient mining capacity of mines, this paper elaborates on the research status of coal and gas outburst and its composite dynamic disaster warning methods and systems in China. The current warning methods and systems for gas outburst and its composite dynamic disasters are mainly developed based on electromagnetic radiation, sound electricity, microseism, and gas concentration time series monitoring technology. Due to differences in coal seam occurrence, mining conditions, and ground stress, the critical values of the warning system indicator system are determined through experience, theory, or laboratory, resulting in low accuracy of the warning results. A mountain of work and regional differences in the critical values of the on-site correction index system directly affect the effectiveness of the early warning system's on-site application. Based on the current situation of coal and gas outburst and its composite dynamic disaster warning methods and systems, as well as the demand for intelligent warning in coal mines, this paper proposes future research prospects: to carry out research on the coupling mechanism of multiple disasters in deep and high-strength mining mines, develop a quantitative dynamic identification model of multiple indicator systems, and achieve integrated monitoring of multiple disasters and coupled disaster or single disaster classification warning; Carry out precise geological exploration and modeling, combined with technologies such as big data and cloud computing, to more accurately capture dynamic disaster indicator parameters and determine critical warning indicator values; By using mathematical methods, the generalized model for qualitative description of the occurrence mechanism of composite disasters is transformed into a quantitative mathematical model, forming a comprehensive warning model of theory, experience, and data, further improving the accuracy of the warning system.