Assessing the conservation status and risk of extinction of species is a major challenge towards biodiversity management. Currently, this is done on a species-by-species basis, a process that requires strong expertise and takes considerable time. Our hypothesis is that it may be possible to infer species conservation status automatically by combining statistical learning, artificial intelligence and ecological modelling approaches. However, hard problems arise, in particular presence-only data, bias and class imbalance.