In this paper we provide a very general framework for studying the return periods of random events depending upon the joint behaviour of two non-independent random variables. We show that using the 2-Copula describing the dependence features of the underlying joint distribution may greatly simplify the calculations, and even yield analytical expressions for the isolines of the return periods. In addition, we introduce the new definitions of primary and secondary return periods, which provide relevant information for performing risk-assessment. The results obtained are extremely important in the applications, where the return period is fundamental during the design phase.