In cost-effectiveness analysis, the incremental cost-effectiveness ratio is used to measure economic efficiency of a new intervention, relative to an existing one. However, costs and effects are seldom known with certainty. Uncertainty arises from two main sources: uncertainty regarding correct values of intervention-related parameters and uncertainty associated with sampling variation. Recently, attention has focused on Bayesian techniques for quantifying uncertainty. We computed the Bayesian-based 95% credible interval estimates of the incremental cost-effectiveness ratio of several related HIV prevention interventions and compared these results with univariate sensitivity analyses. The conclusions were comparable, even though the probabilistic technique provided additional information.