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The aim of the study is to assess the degree of spatial agreement among different patterns of landslide susceptibility maps with almost similar success and prediction rate curves, obtained using different combinations of predictive factors. Our approach was tested in an alpine environment (Italian Alps) where debris flows represent one of the most frequent dangerous processes. A data-driven Bayesian method (the Weights of Evidence modelling technique) was successfully applied, and success and prediction rate curves were computed for supporting the modelling results and assessing the robustness of the models. The values of the area under curves were very similar for different models, ranging from 84.36% to 86.49% for the success rate curves and from 82.46% to 85.66% for the prediction rate curves. Then, the post-probability output maps were classified into rank-based maps, by using an equal-area criterion …