de Vries BCS, Hegeman JH, Nijmeijer W, et al. - This study was sought to construct and compare several models, capable of predicting the risk of major osteoporotic fracture (MOF) as a function of time in patients seen at the fracture and osteoporosis outpatient clinic after sustaining a fracture. This retrospective study included individuals aged > 50 years visiting an FO-clinic. Researchers matched discriminative ability (concordance index) for predicting the risk on MOF with a Cox regression, random survival forests, and an artificial neural network -DeepSurv model. The study included a sum of 7,578 patients, 805 patients sustained a subsequent MOF. The data displayed that predicting the risk of MOF in patients who already sustained a fracture can be done with adequate discriminative performance. A user-friendly tool for risk calculation of subsequent MOF was developed in patients with osteopenia.