The aim of this paper is to report the achievement of Ichnaea, a fully computer-based prediction system that is able to make fairly accurate predictions for Microbial Source Tracking studies. The system accepts examples showing different concentration levels, uses indicators (variables) with different environmental persistence, and can be applied at different geographical or climatic areas. We describe the inner workings of the system and report on the specific problems and challenges arisen from the machine learning point of view and how they have been addressed.