The estimation of cartel overcharges lie at the heart of antitrust policy on cartel proscution as it constitutes a basic element in the determination of fines. Connor and Lande (2008) conducted a survey of cartels and found a mean overcharge estimates in the range of 31% to 49%. By examining more sources, Connor (2010) finds a mean of 50.4% for successful cartels. However, the data used in those studies are estimates obtained in different ways, sources and contexts rather direct observations. Therefore, these data are subject to model error, estimation error and publication bias. A quick glance at the Connor database reveals that the universe of overcharge estimates is asymmetric, heterogenous and contains a number of influential observations. Beside the fact that overcharge estimates are potentially biased, fitting a linear regression model to the data without providing a carefull treatment of the problems raised above may produce distorted results. We conduct a meta-analysis of cartel overcharge estimates in the spirit of Connor and Bolotova (2006) while providing a sound treatment of those matters. We find typical bias-corrected mean and median overcharge estimates of 13.62% and 13.63% for cartels with initial overcharge estimates lying between 0% and 50% and bias-corrected mean and median overcharges estimates of 17.52% and 14.05% for the whole sample. Clearly, our results have significant antitrust policy implications.