Assessing multi-taxon biodiversity is crucial to understand forests’ response to environmental changes and to inform management strategies. In Europe, forest biodiversity monitoring is still scattered and heterogeneous, although a long-term monitoring network has long been advocated. Given the monitoring aims reported in various EU policies, this network should be accurately designed also through the estimation of its sampling effort, here intended as the number of sampling plots and sites. We used a novel database of forest multi-taxon biodiversity for a pilot study to: estimate the minimum sampling effort needed to: assess variation in species richness and composition; compare these estimates with the efforts invested in the pilot database; discuss estimates’ differences across taxonomic groups and forest categories. We focused on six taxonomic groups (vascular plants, birds, epiphytic lichens and bryophytes, wood-inhabiting fungi and saproxylic beetles) across six forest categories. Based on 6,165 plots at 2,084 different locations across Europe, we benchmarked the effort to achieve: a complete species richness estimate through interpolation/extrapolation curves, and a precise evaluation of species composition variation through multivariate standard error. Our estimates differed widely, especially among taxonomic groups. For species richness, estimates range from 3 to 147 plots per site across 3 to 29 sites per forest category, with birds and epiphytic bryophytes requiring the least effort. For species composition, estimates range from 5 to over 25 plots per site across 5 to 20 sites per forest category, with saproxylic beetles, vascular plants, and fungi displaying the highest estimates. The taxonomic groups requiring an effort comparable to existing data were the least diverse, all the others need greater efforts, either for species richness (e.g., saproxylic beetles), or species composition (e.g., vascular plants), or both (e.g., wood-inhabiting fungi). An effective monitoring network of European forests’ biodiversity should thoroughly account for these benchmarks and for their taxon-dependency. Keywords: Birds; Epiphytic lichens; Epiphytic bryophytes; Forest biodiversity; Monitoring network; Multivariate standard error; Rarefaction curves; Saproxylic beetles; Vascular plants; Wood-inhabiting fungi.