It is recommended that easily understandable metrics such as Pearson’s r be employed. Correctional audiences have been found to quickly grasp the practical meaning of treatment and prediction results when presented in the form of Pearson’s r values. Pearson’s r is a very flexible statistic. In addition, it is suggested that null-hypothesis significance testing be abandoned and replaced by confidence intervals and common language statistics that clearly describe the preciseness and magnitude of results. In summary, graphs, along with the plain language statistics described, are essential for describing applied results, and they are most helpful when communicating with the “people who count.” Brief comments are offered on three issues arising in meta-analysis that should be of interest to policymakers; they include: (1) meta-analysis of qualitative reviews, (2) the width of confidence intervals (CIs), and (3) the quality of research design. How is it possible to get influential policymakers and practitioners to attend to the importance of the findings from meta-analyses? Several approaches that will help to ensure that meta-analytic results will have maximum impact are prescribed in this article. Notes, references