Emotional crying is a complex and multifaceted expression that is frequently observed in humans. Its communicative effects have been recently studied in more detail. However, many studies focus on just one specific feature of emotional crying, most often emotional tears, neglecting the complex nature of the expression. Reports about crying episodes observe that tears most commonly occur in combination with other features such as facial expressions, vocalizations, gestures, and varied temporal dynamics. This shortcoming in research is mostly explained by a lack of adequately controlled stimuli depicting different crying features. Here, we provide a solution for this problem by introducing the Emotional Crying Behavior Dataset (ECBD), an openly available resource of 500 videos depicting 10 actors posing variations in tear intensity, facial expression intensity, vocalizations, gestures, and temporal dynamics, and the combination thereof. We present two studies ( N = 2,729) providing evidence for the validity of the dataset. In addition, we developed a static supplementary resource (ECBD-S) with 70 pictures depicting variations in tears and facial expression intensity that was successfully validated across two studies ( N = 601). Overall, our findings support the validity of this new stimulus set that closes a gap in the research on the interpersonal effects of emotional crying. The dataset is openly available for non-commercial research purposes at https://zenodo.org/records/15147817 .