Abstract: With the continuous acceleration of urbanization in China, urban agglomerations, as a new form of spatial agglomeration for urban development, have gradually become a new driving force for promoting high-quality urban development. Therefore, scientific evaluation of the resilience level of urban agglomerations can provide references for the decision-making process. By comprehensively applying the super-efficient SBM model, spatial vector model and barrel theory, this study established an analytical model for the resilience level of urban agglomerations. Subsequently, the Dagum's Gini coefficient, Kernel's density estimation and Markov's chain method were used to analyze the regional differences and spatial and temporal evolution trends of the resilience level of urban agglomeration. Finally, five major urban agglomerations in China were selected as research cases for empirical study. The results showed that the resistance and resilience capacity of provincial capitals and municipalities directly under the central government presented a two-level differentiation trend, while the adaptation and comprehensive resilience construction were relatively good; The resilience level of the five major urban agglomerations showed a clear overall spatial pattern of high in the east and low in the west, with coastal areas higher than inland areas. Among them, the average resilience of the Beijing-Tianjin-Hebei urban agglomerations was the lowest, and the weak board effect within the agglomeration was the most obvious; Except for the Beijing-Tianjin urban agglomeration, the differences in Gini coefficients within other urban agglomerations had decreased, with the most significant differences in resilience levels between the Beijing-Tianjin-Hebei and Chengdu-Chongqing urban agglomerations; The overall resilience level of the five major urban agglomerations showed a decreasing trend in dispersion, but there was still a significant Matthew effect. By considering spatial factors, there existed a significant spatial spillover effect in the Beijing-Tianjin-Hebei urban agglomeration.