A simulation-based reliability analysis method is presented and evaluated. This method is intended for problems for which most probable point of failure (MPP) search-based methods fail or provide inaccurate results, and for which Monte Carlo simulation and its variants are too costly to apply. This may occur in the evaluation of complex engineering problems of low failure probability. The method used to address this problem is a variant of conditional expectation and works by sampling on the failure boundary without relying on the MPP. The effectiveness of the method is compared to a selection of other commonly available reliability methods considering a variety of analytical as well as more complex engineering problems. The results indicate that the method has the potential to deliver solutions of high efficiency and accuracy for a wide range of difficult reliability problems.