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Convective storms that produce large hail are among the most damaging natural hazards and globally losses due to these events are increasing. To evaluate and quantify the potential risk associated with these storms, hail climatologies are created from historical records. Unfortunately, a comprehensive analysis of the Netherlands does not exist.The aim of this study is to create a hail climatology of the Netherlands and report on spatial and temporal hail risk by combining two approaches. The first approach relies on written documents containing information on historic events collected from Weerspiegel-magazine and the European Severe Weather Database (ESWD), from the time period 1974-2019. The second approach utilizes radar-data from the time period 2008-2019 and implements a radar-based Hail Detection Algorithm (HDA) to estimate hailstone sizes.From a total of 7559 report-based observations in the time period 1974 -2019, it is found that 81% of severe hail events are observed in the months from May to August with the majority (53%) reported between 14:00 and 19:00 local time. The return period estimation from the observed hail sizes indicates an occurrence of 1 in 100 years in the case of diameter equal or larger than 11 cm and 1 in 10 years of diameter equal or larger than 7 cm for the Netherlands. It is found that the Northern NUTS region of the Netherlands is 3.5 times less likely to experience a hailstone of 6 cm than the Southern NUTS region. The radar-derived hail observations show an increasing gradient in the number of (severe) hail days going from the Northwest to the Southeast. Additionally, the latter region shows the highest averaged values of Maximum Estimated Size of Hail (MESH). By clustering hail events into individual storms, an increasing trend in MESH values was observed with increasing hailstorm extent, though large hailstone sizes can also occur in small hail streaks. To further extend knowledge on this topic, it is recommended to conduct quantitative research on the effect of climate change on the formation of severe hail and possibly apply synthetic data to generate longer records. Moreover, recommendations are made to improve short-term measures against hail damage by developing nowcast systems and potentially combining these with real-time information from social media.