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The spatial distribution of shallow landslides is strongly influenced by different climatic conditions and environmental settings. This makes difficult the implementation of an exhaustive monitoring technique for\ud correctly assessing the landslide susceptibility in different environmental contexts. In this work, a unique methodological strategy, based on the statistical implementation of the generalized additive model (GAM), was performed. This method was used to investigate the shallow landslide predisposition of four sites with different geological, geomorphological and land-use characteristics: the Rio Frate and the Versa catchments (Southern\ud Lombardy) and the Vernazza and the Pogliaschina catchments (Eastern Liguria). A good predictive overall accuracy was evaluated computing by the area under the ROC curve (AUROC), with values ranging from 0.76 to 0.82 and estimating the mean accuracy of the model (0.70–0.75). The method showed a high flexibility, which led to a good identification of the most significant predisposing factors for shallow landslide occurrence\ud in the different investigated areas. In particular, detailed susceptibility maps were obtained, allowing to identify the shallow landslide prone areas. This methodology combined with the use of the rainfall thresholds \ud for triggering shallow landslides may provide an innovative tool useful for the improvement of spatial planning and early warning systems

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