This paper presents a probabilistic framework to assess the stability of unsaturated slope under rainfall. The effects of soil spatial variability on the probability of rainfall-induced slope failure (landslides) are investigated. Soil spatial variability is considered by modeling the saturated hydraulic conductivity of the soil (k(s)) as a stationary lognormal random field. Subset simulation with a modified Metropolis-Hastings algorithm is used to estimate the probability of slope failure. It is demonstrated numerically that probabilistic analysis accounting for spatial variability of k(s) can reproduce a shallow failure mechanism widely observed in real rainfall-induced landslides. This shallow failure is attributed to positive pore-water pressures developed in layers near the ground surface. In contrast, analysis assuming a homogeneous profile cannot reproduce a shallow failure except for the extreme case of infiltration flux being almost equal to k(s). Therefore, ignoring spatial variability leads to unconservative estimates of failure probability. The correlation length of k(s) affects the probability of slope failure significantly. The applicability of subset simulation with a modified Metropolis-Hastings algorithm to assess the reliability of problems involving spatial variability is highlighted. (C) 2011 Elsevier Ltd. All rights reserved.