In contingent planning under partial observability with sensing actions, the solution can be represented as a plan tree, branching on various possible observations. Typically, one seeks a satisfying plan leading to a goal state at each leaf. In many applications, however, one may prefer some satisfying plans to others. We focus on the problem of providing valid comparative criteria for contingent plan trees and graphs, allowing us to compare two plans and decide which one is preferable. We suggest a set of such comparison criteria-plan simplicity, dominance, and best and worst plan costs. In some cases certain branches of the plan correspond to an unlikely combination of mishaps, and can be ignored, and we provide methods for pruning such unlikely branches before comparing the plan graphs. We explain these criteria, and discuss their validity, correlations, and application to real world problems. We suggest efficient algorithms for computing the comparative criteria. We provide experimental results, showing that plans computed by existing contingent planners can be compared using the suggested criteria.