Unmotivated test takers using rapid guessing in item responses can affect validity studies and teacher and institution performance evaluation negatively, making it critical to identify these test takers. The authors propose a new nonparametric method for finding response-time thresholds for flagging item responses that result from rapid-guessing behavior. Using data from a low-stakes assessment of college-level academic skills as an illustration, the authors evaluate and compare model fit and score estimation based on data sets cleaned by both new and existing methods. Flagging rapid-guessing responses is found to generally improve model fit, item parameter estimation, and score estimation, as in the literature. This new method, based on both response time and response accuracy, shows promise in detecting rapid guessing and in improving efficiency of the flagging process when built into data analysis.