Rainfall threshold is a widely used method for estimating minimum critical rainfall amount which can yield a slope failure. Literature reviews show that most of the threshold studies are subjective and not optimal. For this study, effective rainfall was considered for threshold definition. Support vector machines (SVM) and automatic event identification were used in order to establish an optimal and objective threshold for the Séchilienne landslide. Effective rainfall does significantly improve threshold performance (misclassification rate of 7.08 % instead of 13.27 % for gross rainfall) and is a relevant parameter for threshold definition in deep-seated landslide studies. In addition, the accuracy of the Séchilienne SVM threshold makes it appropriate to be integrated into a landslide warning system. Finally, the ability to make predictions at a daily time step opens up an opportunity for destabilisation stage predictions, through the use of weather forecasting.