Wetlands and their unique biodiversity are threatened by drainage, agricultural conversion, and climate change. Spatial species-level biodiversity modelling help identifying effective conservation measures. However, existing species-level models for wetland vegetation are often geographically limited, miss variables for hydrological conditions and neglect moss species, essential to many wetlands. Thus, we aimed to develop and validate a species-level biodiversity model for wetland vegetation across Europe. We fitted and cross-validated species distribution models (SDMs) for 265 vascular plant and moss species characteristic of European wetlands, using environmental variables representing climate, soil, hydrology and anthropogenic pressures. We validated the spatial predictions of the SDMs with independent dataset from the Global Biodiversity Information Facility (GBIF) and the niche optima of the species, as obtained from the modelled species response curves, with empirical niche optima. The cross-validation and validation with GBIF revealed good predictive power of the SDMs, especially for diagnostic mosses. Median cross-validated values of AUC and TSS equalled 0.93 and 0.73, respectively, and median true positive rate (TPR) equalled 0.77. SDMs of diagnostic vascular plants performed well too, with median AUC, TSS and TPR of 0.91, 0.69 and 0.67, respectively. SDMs of non-diagnostic plants had the lowest performance, with median AUC, TSS and TPR values of 0.84, 0.54 and 0.62, respectively. Correlations between modelled and empirical niche optima were typically in the expected direction. Climate variables, in particular the mean temperature of the coldest month, were the most important predictors of species occurrence. In addition, groundwater table depth was an important predictor for diagnostic vascular plants, but not for mosses. We conclude that our SDMs are suitable to predict broad-scale patterns of wetland plant species distributions as governed by climatic conditions. Alternative or additional variables or a different modelling approach might be needed to better represent the local heterogeneity in hydrological conditions of wetlands