Pediatric trials are often conducted later in the drug development process, after data in the adult population has become available. The question of how to incorporate the adult data, as well as other external data, in pediatric trials can be complex as the relationship between drug performance in adult and pediatric patients has usually not been established. In this talk, we will compare the operating characteristics of proposed pediatric designs that utilize various degrees of partial extrapolation via informative priors of a Bayesian analysis. Incorporating prior information can reduce the sample size of the study with minimal increases in the false positive rate, which will enable fewer pediatric patients to be exposed to experimental conditions in order to answer the key scientific questions of the trial. The potential smaller sample size of a Bayesian design is particularly advantageous for pediatric trials where enrollment may be challenging.