A key question in conditional planning is: how many, and which of the possible execution failures should be planned for? One cannot, in general, plan for all the possible failures because the search space is too large. One cannot ignore all the possible failures, or one will fail to produce sufficiently flexible plans. In this paper, we describe an approach to conditional planning that attempts to identify the contingencies that contribute the most to a plan’s overall utility. Plan generation proceeds by handling the most important contingen-cies first, extending the plan to include actions that will be taken in case the contingency fails. We discuss the representational issues that must be addressed in order to implement such an algorithm, and present an example which illustrates our approach.