In this work, we propose a novel approach to solve probabilistic planning problems taking into account the risk that the decision maker is ready to accept regarding the probabilities of reaching the goals. Our approach guarantees that the probability of reaching a state satisfying the selected goals is above a certain limit threshold. To achieve this, we relax the constraints that all goals must be satisfied, and select the most valuable set of goals whose reachability probability is above the threshold. To this end, we propose a goal selection heuristic based on the reachability probability and the cost between goals that are estimated using an abstracted version of the problem. Finally, a planetary exploration problem will be used for illustrating the effectiveness of the proposed approach. Our results show that the obtained selections cover the most valuable possible goals and respect the reachability probability threshold.