<p>Resilience assessment of soil slopes against rainfall infiltration is an effective tool for the mitigation of rainfall-induced landslides. However, the research in this direction is still in preliminary stage. This study suggests a novel probabilistic framework for assessing slope resilience to rainfall during a given exposure time. First, the functional state of slopes is determined according to slope stability analysis under rainfall. The total recovery time of slopes after failure due to rainfall within the exposure time is used to define the resilience metric. Then, the uncertainties of rainfall events occurring within an exposure time, soil parameters and the recovery time of slopes after failure caused by rainfall are modelled, respectively. The mean value and coefficient of variation of the resilience of slopes over the exposure time are estimated via Monte Carlo simulation. To enhance the computational efficiency, the support vector machine is utilized to construct a surrogate model for slope failure prediction. Finally, the proposed framework is demonstrated with an illustrative soil slope subjected to rainfall infiltration. The results show that both the total recovery time and the resilience of the slope follow the bimodal distribution. When the exposure time becomes longer, the mean total recovery time of the slope significantly increases while the mean resilience of the slope remains almost identical. Overall, this study provides new insights into the assessment of slope resilience under rainfall conditions.</p>