Under the background of global climate change and the rapid development of urbanization, the urban extreme precipitation events, urban rainstorm and flood disasters occur frequently, and flood disaster losses are serious. How to make decision support service is the key problem of emergency management of urban rainstorm and flood disasters. In consideration of the existing problems in the emergency management decision-making of urban rainstorm and flood disasters in China, this paper put forward the decision-making method of urban rainstorm and flood disasters emergency management based on similar cases analysis method. According to the evolution process of urban rainstorm and flood disasters, the attribute system of urban rainstorm and flood disasters was established. Entropy weight method was used to calculate the weights of problem attributes. The case-based reasoning method was used to calculate the similarities of problem attribute eigenvalues between the target case and the historical cases. According to the problem attribute weights and attribute similarities, the global similarity was determined. The case-based decision theory method was used to calculate the similarities between the target case and the historical cases. According to the comprehensive evaluation values of the alternative cases, the optimal alternative cases were determined. The methods proposed were further verified using typical urban rainstorm and flood disaster events in Xi'an city as an example. Results show that: the case-based reasoning method was used to obtain the highest similarity of historical case P3, the case-based decision theory method was used to obtain similar case set {P3, P4}. By comparing the calculation results of the case-based reasoning method and the case-based decision theory method, the case-based decision theory method is more suitable for the optimization of urban rainstorm and flood disaster emergency plans. The research results can provide scientific basis for emergency management of urban rainstorm and flood disasters.