The adoption of agri-environment practices (AEPs) is crucial for safeguarding the long-term sustainability of ecosystem services within European agricultural landscapes. However, the tailoring of agri-environment policies to the unique characteristics of farming systems is a challenging task, often neglecting local farm parameters or requiring extensive farm survey data. Here, we develop a simplified typology of farming system archetypes (FSAs), using field-level data on farms’ economic size and specialisation derived from the Integrated Administration and Control System in three case studies in Germany, Czechia and the United Kingdom. Our typology identifies groups of farms that are assumed to react similarly to agricultural policy measures, bridging the gap between efforts to understand individual farm behaviour and broad agri-environmental typologies. We assess the usefulness of our approach by quantifying the spatial association of identified archetypes of farming systems with ecologically relevant AEPs (cover crops, fallow, organic farming, grassland maintenance, vegetation buffers, conversion of cropland to grassland and forest) to understand the rates of AEP adoption by different types of farms. Our results show that of the 20 archetypes, economically large farms specialised in general cropping dominate the agricultural land in all case studies, covering 56% to 85% of the total agricultural area. Despite regional differences, we found consistent trends in AEP adoption across diverse contexts. Economically large farms and those specialising in grazing livestock were more likely to adopt AEPs, with economically larger farms demonstrating a proclivity for a wider range of measures. In contrast, economically smaller farms usually focused on a narrower spectrum of AEPs and, together with farms with an economic value <2 000 EUR, accounted for 70% of all farms with no AEP uptake. These insights indicate the potential of the FSA typology as a framework to infer key patterns of AEP adoption, thus providing relevant information to policy-makers for more direct identification of policy target groups and ultimately for developing more tailored agri-environment policies.