TREAT is a decision support system for antibiotic treatment in inpatients with common bacterial infections. It was tested in a randomised controlled trial in three countries and shown to improve the percentage of appropriate empirical antibiotic treatments, while at the same time reducing hospital stay and the use of broad-spectrum antibiotics. TREAT is based on a causal probabilistic network and uses a cost-benefit model for antibiotic treatment, including costs assigned to future resistance. In the present review we discuss the advantages of using causal probabilistic models for prediction and decision support, and the various decisions that were taken in the TREAT project.