We present a prior-knowledge based shadow prediction model, focused on outdoors scene, which allows to predict pixels, on the camera, which are likely to be part of shadows casted by surrounded buildings. We employ a geometrical approach which models surrounding buildings, their shadow and the camera. One innovative aspect of our method is to retrieve building datas automatically from OpenStreetMap, a community project providing free geographic data. We provide both qualitative and quantitative results in two different contexts to assess performance of our prediction model. While our method cannot achieve pixel precision easily alone, it opens opportunities for more elaborate shadow detection algorithms and occlusion-aware models.