AbstractDetermining association rules of significant interest is an essential task within data mining and statistical analysis. In this paper, we first precisely define the notion of association rule. For this, we introduce a general model, which includes the usual transaction model, and which allows many operations on the association rules. Then, we interpret association rules as statistical decision rules. This interpretation leads to four decisional measures, one of them being the usual confidence. Then, we give some strategies based on the use of these four decisional measures in order to select or to construct association rules with a given consequent. We finally present an experimental study to illustrate these strategies. This study is carried out in R language, with the R‐package we specifically built for association rules mining.