Online advertising is becoming more and more competitive. Hence, to maximize their revenue by optimizing their KPI (Key Performance Indicators) such as the CTR (Click-Through-Rate), advertisers use various targeting techniques. On the one hand, targeting can be based on the contextual information of the current webpage page visited by the users, and on the other hand it can be performed by profiling the users’ historical set of queries. The latter technique is known as Behavioral Targeting (BT). This approach is used to predict whether a user would be more or less sensitive to advertising. We present here a BT system based on logistic regression. However we shall begin this paper by presenting some technical concepts used in digital advertising.