Although precision medicine is at least partially realized in dermato-oncology, the field of dermatoimmunology comprising inflammatory skin diseases is only at the step from traditional toward stratified medicine. This lack of innovation leaves clinically relevant questions unanswered, including predicting the personal likelihood of therapeutic success as well as the risk of drug-related adverse events or the development of comorbidities. The translational dermatology initiative hypothesizes that these shortcomings are due to the subjective nature of the current disease ontology, which does not address the heterogeneity and dynamics of diseases. By integrating deep clinical phenotyping and repetitive multiomics analyses of tissue and circulation of patients covering the whole spectrum of chronic skin inflammation independent of the traditional disease nomenclature, the translational dermatology initiative creates a high-quality dataset optimized for machine learning. The aim of the translational dermatology initiative is to reclassify inflammatory skin diseases on the basis of objective molecular events that enable prediction of clinically meaningful outcome variables. The translational dermatology initiative is currently recruiting at 2 centers (Freiburg and Stockholm), with the aim to expand this into a global initiative.