This paper is a review of the decision tree methodology. This is a very useful technique in complex decision making, when the consequences of the decisions are distant in time and the information upon which we can rely is uncertain. Decision trees are the basic structure underlying most applications of decision analysis in medicine. However, in this review we only cover their application to the pharmaco-economic field. The main steps of this decision analysis are explained. Thereafter, a case study from the literature is used as an example, i.e. an application of the decision tree analysis to a study aimed at comparing two different drugs in the treatment of gastro-esophageal reflux. The main focus of our paper is on the statistical aspects, which include the definition and quantification of the outcome variables, the definition and quantification of the probabilities of occurrence of the uncertain events considered in the decision tree, and the sensitivity analysis. The knowledge of the basic laws of the probability theory is mandatory for assigning correct values to the parameters of the decision tree (outcomes and probabilities). Finally, the sensitivity analysis is an important part of the work to be performed in the last stage of the decision analysis in order to measure the degree of robustness of the results when varying the assumptions.