Uranium is the basic raw material for nuclear energy and is quite highly regarded. Developing a safe supply of uranium is important for safeguarding sustainable nuclear development. The purpose of this study is to evaluate the sustainability of uranium development in China based on dynamic system modeling combined with GAN (Generative Adversarial Network) analysis. We considered eight essential indicators and 42 sub-indicators as part of a detailed quantitative description, and then developed a framework to evaluate and rank China-specific sustainability in light of the quantitative performance of five options for fuel cycle transition scenarios. We began by using KMO sample measurements and the Bartlett Test of Sphericity to determine the suitability of factor analysis and the fitness of the corrected model map and observation data. We then analyzed the roles of different representatives of the decision makers and their impacts on the overall ranking by applying GAN methods from a weighted perspective. Five transition scenarios identified are 1) Pressurized Heavy Water Reactors, 2) Mixed Light Water Reactor + Fast Reactor, 3) Mixed LWR+FR fuel cycle scheme with heterogeneous irradiation, 4) Mixed Pressurized Water Reactor + FR fuel cycle scheme with plutonium recycled directly and repeatedly, and 5) Sodium-cooled fast breeder reactor power plant. The results showed that scenario 1 is the most unsustainable and highly confrontational scenario with a high demand for uranium resources, the lowest sustainability and a high level of antagonism among departments. On the other hand, Scenario 5 requires more advanced technology but exhibits less antagonism among the departments, and thus it largely satisfies the basic requirements for uranium sustainability and low levels of antagonism. In this paper, a safety assessment index system for the uranium supply is computed using a GAN framework. This system plays a crucial role in the sustainable supply and development of uranium, and provides flexibility for coping with the evolution and inherent uncertainties of the necessary technological developments.