The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) is often evaluated in randomized clinical trials-where individuals are nested within clusters, for instance patients in general practices. In such two-level cost effectiveness trials, one can randomly assign treatments to individuals within clusters (multicentre trial) or to entire clusters (cluster randomized trial (CRT)). Such cost-effectiveness trials (CRTs and multicentre trials) need careful planning to evaluate the cost-effectiveness of interventions within the available financial research resources. The optimal number of clusters and the optimal number of subjects per cluster for both types of cost-effectiveness trials can be determined by using optimal design theory. After presenting some theoretical results on how to calculate samples sizes for these designs, the presentation will continue with a description of a user-friendly computer program SamP2CeT (Sample size and Power calculation for 2-level Cost-effectiveness Trials) enabling researchers to design cost-effectiveness trials with regard to the optimal number of clusters and the optimal number of subjects per cluster. In case of insufficient knowledge on model parameters, the computer program SamP2CeT also provides numbers of clusters and numbers of subjects per cluster starting from a maximin strategy. SamP2CeT can either be used to calculate the minimum budget for a desired level of power, or the largest power for a fixed budget. The computer program will be illustrated for two empirical studies from the literature on cost-effectiveness trials.