The application provides a crack seismic attribute judging system and a crack seismic attribute judging method. The method comprises the following steps: identifying and calculating out crack information of single-well crack density according to acquired imaging logging data and core analysis data, and generating a single-well crack model; extracting seismic attribute data of a specified type from acquired seismic data, and selecting an optimal seismic attribute of which the correlation with the reservoir meets a preset requirement; building a training model by taking the single-well crack model as an input signal and the optimal seismic attribute as an output signal; using an artificial intelligence nonlinear neural network to train the training model; and when the optimal seismic attribute in the training model meets a set screening condition, outputting the optimal seismic attribute meeting the set screening condition. According to the embodiments of the application, the advantages and disadvantages of numerous seismic attributes can be identified intelligently, quickly and accurately, well detection cracks can be identified effectively based on seismic attributes, and the effect and efficiency of actual operation are improved greatly.