According to the application requirements of target recognition, task programming and template preparation, an algorithm of scene identifiability analysis based on evidential networks was proposed to realize the quantitative analysis of the scene identifiability degree. After having acquired the support data of the research area and setting the imaging parameters, a certain number of salient ground objects were extracted as the scene nodes from the data. Then, the identifiability degree of each extracted object was assessed from three aspects, including scale significance, shape uniqueness and visualization. After that, the conditional belief function which represented the mutual support degree between scene nodes was defined by the contour point number of the extracted objects. Finally, the analysis results of the scene identifiability were obtained by the reasoning and fusion ability of evidential networks. Experimental results demonstrate that the algorithm of scene identifiability analysis is reasonable and effective, which meets the requirements of mission planning and thus exhibits great practical value.