With the overall victory of poverty alleviation in China, the focus of rural work has been transformed into rural revitalization. Therefore, based on the panel data of 30 provinces and cities in China spanning 2011 to 2019, this research used the entropy-TOPSIS method to calculate the weights of each index of the two rural revitalization and green finance systems. This research also constructs the spatial Dubin model to empirically analyze the direct effects and spatial spillover effects of green finance development on the level of rural revitalization. Additionally, this research calculates the weight of each indicator of rural revitalization and green finance using entropy-weighted TOPSIS. This research reveals that the current state of green finance is not conducive to increasing local rural revitalization and does not significantly affect all provinces. Further, the number of human resources can improve the local level of rural revitalization, not the entire province. These dynamics benefit the growth of local rural revitalization in the surrounding areas if employment and technology levels are developed domestically. Moreover, this research reveals that education level and air quality have a spatial crowding effect on rural revitalization. Thus, when developing rural revitalization and development policies, it is vital to prioritize the high-quality development of finance to be closely monitored by local governments at the respective levels. Furthermore, the stakeholders must pay critical attention to the connection between supply and demand and between financial institutions and agricultural enterprises in the provinces. Again, the policymakers must also increase policy preference, deepen regional economic cooperation, and improve the supply of essential rural elements to play a more significant role in green finance and support rural revitalization.