This paper presents our activities towards the development of a clinical decision support (CDS) system for the early diagnosis of pregnancies of unknown location (PULs). PULs are pregnancies that are not visualized on ultrasound. Generally, they turn out to be failing, normal intra-uterine, or ectopic pregnancies. Using 856 PULs collected at a London hospital, we developed probabilistic multi-class models. At the moment, a large multi-center data set is being collected. Data are entered using stand-alone software, and are sent to the database server by ftp. These data will be used to prospectively test existing models, and to build new, hopefully more robust, models. The ultimate aim is to select one model for implementation in a CDS system that is easy to use in routine clinical practice.