The human personality predicts a wide range of activities and occupational choices—from musical sophistication to entrepreneurial careers. However, which method should be applied if information on personality traits is used for prediction and advice? In psychological research, group proﬁles are widely employed. In this contribution, we examine the performance of proﬁles using the example of career prediction and advice, involving a comparison of average trait scores of successful entrepreneurs with the traits of potential entrepreneurs. Based on a simple theoretical model estimated with SOEP data and analyzed with Monte Carlo methods, we show, for the ﬁrst time, that the choice of the comparison method matters substantially. We reveal that under certain conditions the performance of average proﬁles is inferior to the tossing of a coin. Alternative methods, such as directly estimating success probabilities, deliver better performance and are more robust.