In this study, a method of fast estimation of stability margin based on clustering is proposed integrating the traditional causal analysis method and data core thinking method. Firstly, from the massive historical quantitative analysis or simulation calculation results, the transient stable mode is extracted according to faults, and the stable mode of all faults is taken as the key characteristic quantity. Secondly, each fault is clustered according to characteristic quantity to generate safe operation knowledge base. Finally, based on the knowledge base, each fault in the current mode is automatically matched and the stability margin is quickly estimated. This method improves the speed of analysis and calculation, provides a basis for the rapid decision-making of power network security and stability, and provides a new idea for the analysis and evaluation of power system transient stability.