The use of dynamic risk factors to predict recidivism is important because it is argued that static factors cannot adequately account for changes in that occur in risk over time. This research tests this argument by examining the improvement in predictive accuracy when dynamic risk factors are added to the criminal history scale in the ORAS community supervision tool. Results and implications will be discussed.