Predicting likely software defects in the future is valuable for project managers when planning resource allocation for software testing. But building prediction models using only code metrics may not be suffice for accurate results. In this work, we investigate the value of change-related metrics that can be collected from the project's version archives for the purpose of defect prediction. Our results suggest that prediction models built using change metrics are at least as good as those using code metrics, and sometimes even outperform them