This paper presents a probabilistic slope stability analysis approach that formulates the slope failure event as a series of mutually exclusive and collectively exhaustive events using conditional probability and utilizes Monte Carlo simulation (MCS) to determine the occurrence probability for each of the mutually exclusive and collectively exhaustive events in a progressive manner. The probabilities of each event are aggregated to represent the overall slope failure probability pf. The pf values obtained from the proposed approach are shown to agree well with those pf values that have been obtained by searching a large number of potential slip surfaces for the minimum factor of safety in each MCS sample. The computational efficiency, however, is shown to improve by, at least, an order of magnitude. In addition, the approach identifies the key failure modes (i.e., those slip surfaces that have significant effects on pf) which can be readily used in the mitigation of landslide risk.