The Radboud Faces Database (RaFD) is a freely available database of Caucasian face images that vary systematically in facial expressions, gaze direction, and head orientation. It includes images of both adult and child models, with controlled technical aspects such as facial landmarks, lighting, and background. The database was developed to provide standardized stimuli for research in face processing, emotion, and social cognition. The images were captured in a controlled environment using five Nikon cameras and three flashes, with models practicing expressions and being coached by FACS specialists to ensure accurate and consistent expressions. The database was validated using ratings from 276 participants. Participants rated the facial expressions, intensity, clarity, genuineness, and valence of the images. The results showed high agreement between the intended and chosen expressions, with an overall agreement rate of 82%. Happiness was the most accurately recognized expression, while contempt was the least accurate. The validation also revealed systematic patterns of deviating choices for surprise, fear, and disgust, with morphological overlaps between intended and alternative expressions. The RaFD provides a parametric set of face images that can be used in various research domains, including developmental research, social referencing, and human-computer interaction. It is freely available for scientific research and includes online support materials with average validation data. The database is an important resource for researchers requiring standardized, controlled facial stimuli with systematic variations in key facial characteristics.The Radboud Faces Database (RaFD) is a freely available database of Caucasian face images that vary systematically in facial expressions, gaze direction, and head orientation. It includes images of both adult and child models, with controlled technical aspects such as facial landmarks, lighting, and background. The database was developed to provide standardized stimuli for research in face processing, emotion, and social cognition. The images were captured in a controlled environment using five Nikon cameras and three flashes, with models practicing expressions and being coached by FACS specialists to ensure accurate and consistent expressions. The database was validated using ratings from 276 participants. Participants rated the facial expressions, intensity, clarity, genuineness, and valence of the images. The results showed high agreement between the intended and chosen expressions, with an overall agreement rate of 82%. Happiness was the most accurately recognized expression, while contempt was the least accurate. The validation also revealed systematic patterns of deviating choices for surprise, fear, and disgust, with morphological overlaps between intended and alternative expressions. The RaFD provides a parametric set of face images that can be used in various research domains, including developmental research, social referencing, and human-computer interaction. It is freely available for scientific research and includes online support materials with average validation data. The database is an important resource for researchers requiring standardized, controlled facial stimuli with systematic variations in key facial characteristics.