The effect of unplanned downtime cannot be more over emphasized which can range from minor disturbance to catastrophic to plant operation. As much as possible the occurrence of failure has to be reduced or eliminated by putting more focus on planned downtime. This initiative can be accomplished by predicting the equipment failure accurately such that appropriate preventive actions can be planned and taken in order to minimize the failure as wells as the impact of equipment failure. However, accurate prediction depends highly on data availability and data scarcity remains one of the main challenges in applying reliability analysis. This paper presents the use of experts' tacit knowledge in the analysis to predict the probability of occurrence of system failure. This is done through the integration of expert elicitation, analytical hierarchical process (AHP) and least squared method to estimate the system failure distribution from which other reliability measures can be derived. The result showed statistical equivalence at 90 confidence level compared with estimation based on failure data proving the validity of the method in cases where failure data is unavailable. © 2014 Owned by the authors, published by EDP Sciences.