Often in dose-finding studies, though the objective is to determine a dose for future development, there's concern about prolonged exposure of patients to doses that do not provide benefit. Futility rules can be built into the design to prevent such a scenario. Here we present a Bayesian approach to evaluate the study outcome during the conduct of the trial, i.e., multiple interim analyses to inform dropping futile doses in a dose-finding study. This Bayesian approach relied on the calculation of Bayesian predictive probability (BPP) defined for the primary efficacy endpoint for each dose arm at repeated interim looks. With normal distribution assumption for the observed data for the primary efficacy endpoint and a conjugated, non-informative normal prior distribution for parameters, a closed-form equation for BPP is available (Dmitrienko and Wang, 2006). This allows the calculation of BPP to be easily performed using commonly available software such as SAS or R. A futility rule based on the BPP was defined and the operating characteristics of the Bayesian approach were evaluated in the context of our Phase 2 dose-finding study.