**Background** Facial expressions are a universal language of emotions, and include the expression of several basic emotions like happiness, sadness, anger, fear, surprise and disgust.1 Facial expression recognition (FER) develops between infancy and early adulthood and is modulated by gender. 2, 3 The ability to identify these facial emotions is crucial for social functioning.4 Faces are often encountered and FER serves important roles in numerous daily life domains. Therefore, developmental research is eager to use facial expressions as stimuli. To improve the meaningfulness of this research, a validated face database is needed. At the moment, several validated adult databases exist (e.g., FACES 5; KDEF 6; ADFES 7). One of these databases is the Radboud Faces Database (RaFD 8). The RaFD is a picture set of 67 models, including Caucasian men, women and children, and Moroccan-Dutch men, with each model displaying eight emotional expressions (anger, disgust, fear, happiness, sadness, surprise, contempt, neutral). The RaFD includes high quality pictures, and is more extensive than the Ekman-Friesen Pictures of Facial Affect (EFPCA 9), FACES 5 and KDEF 6 because it includes contempt. This is considered to be an important emotion too, because it is widely used and recognized.10 Additionally, the RaFD models have modern haircuts and neutral clothing (when compared to the EFPCA 3). Currently, the Caucasian adult and child faces of the RaFD are validated by adults, who mostly agreed on the expressed emotions. 8 Furthermore, children have validated the child faces (unpublished data). However, it would be valuable if children validated the Caucasian adult faces too, because many studies with children employ adult faces as stimuli, without validated norms. Such a norm would provide an absolute baseline for children’s FER, and improve the validity of future research using adult facial expressions. Importantly, ‘children’ do not form a homogenous group; earlier research reported important distinctions in FER performance between girls and boys and between different ages. First, gender differences in FER could result from different socialization towards girls and boys, since girls receive more encouragement to develop their emotional intelligence.11,12 Correspondingly, a meta-analytic review of FER in children showed a small but robust female advantage with large effect sizes in infancy. 12 Differences were explained by different neurologic maturation, and smaller effect sizes in middle and late childhood. Although some later experiments did not find that girls outperformed boys,13 the overall female advantage in FER seen in adults8 seems to be present for children as well. Second, FER performance increases with age, for which various explanations exist. A differentiation account of emotional categories explains the improvement of FER with age by increasingly specific categorization of emotions.2 The ability to distinguish specific emotions is still developing, even in young adolescents, who still develop their visual ability to distinguish and integrating contours. These developmental patterns suggest continuous development of subtle FER.14 In accordance with aforementioned theories, studies found constant development in later childhood 2, 15, 16 although it should be noted that there are also studies that did not find this pattern.17, 18 E.g., The study of Lawrence et al. (2016), who used the adult EFPCA pictures in a forced-choice paradigm, found a positive linear trend in the development of FER in 6 to 16 year olds (N = 478), but between 8 and 13 year there was no significant improvement of FER-accuracy. Specifically, children of 8-13 years old could identify happiness, sadness, anger and - in contrast to 7-year-olds - surprise. Disgust was not accurately recognized until the age of 14, and fear was only recognized accurately in 16 year old children. **Research Aim** The goal of this study is to validate the adult faces in the RaFD for children by examining to what extent boys and girls of different ages agree on the expressed emotions, the models’ attractiveness, and valence and clarity of the expressed emotions. Finally, we will investigate the role of gender and age in FER. **Hypotheses** Based on the results from the children’s rating of children’s faces (unpublished data), it is hypothesized that: (1) children will highly agree on the expressed emotion, model attractiveness, valence and clarity, and (2) agreement and clarity will be significantly higher for happiness than for all other emotions. 14, 16, 19 . For disgust and fear (Lawrence et al., 2016), it will be significantly lower than all emotions except contempt, for which it will be lowest (because even adults find this difficult,10, 2 Langner et al., 2010). Based on previous studies, we expect that accuracy of face recognition in general will increase with age and that girls are better at emotion recognition than boys (small effect). **Planned sample size** 560 children from grades three to six, between eight and thirteen years old, will be recruited from Dutch elementary schools. **Procedure** The procedure will closely follow the procedure of the first study (unpublished data) that validated the child models of the RaFD in the same age group. The study will be conducted in classrooms at Dutch elementary schools. Children will be placed in a way that prevents them from copying other children’s answers, and will complete the tasks under supervision of the researchers. After a short introduction, the researchers remind the children of their rights as participants, to raise their hands if they have questions, and to only answer what they think is right. Next, the researchers will explain the RaFD validation task. Children will receive the booklets for the RaFD validation task and then complete this task group-wise. Each class of every school will be randomly assigned to one of the ten versions of the RaFD.After having completed the RAFD validation study, the children will individually complete an interpretation bias task, the SASC-R, CDI and a sociometrics questionnaire. These parts will not be further explained, as they will not be used for the current study. Finally, children will fill out the demographic questionnaire on laptops. The total study will take approximately one hour. **Analysis plan** If children show overall answering patterns indicating misunderstanding or indifference, they will be excluded from further analyses. Data analyses will closely follow the analyses as performed by Langner et al. (2010). This will roughly consist of four steps: Step 1: Overall percentage raw hit rates. Repeated measures ANOVA with unbiased hit rates. Factor: intended emotions (levels: happiness, neutral, anger, sadness, surprise, fear, disgust) Step 2: Intra-Class Correlations (ICC’s) for Attractiveness, Valence, and Clarity. Two seperate one way ANOVAs for clarity and valence Factor: intended emotion. Outcome: clarity, valence and attractiveness. Step 3: Two repeated measures ANOVAs with Within- subjects factor: Intended emotions [happiness, neutral, anger, sadness, surprise, fear, disgust]. 1: with Between- subjects factor: Gender (dummy coded) 2: with Between- subjects factor: Age **References** 1 Ekman, P., & Friesen, W. V. (1971). Constants across cultures in the face and emotion. Journal of Personality and Social Psychology, 17(2), 124-129. doi: 10.1037/h0030377 2 Bullock, & Russell, J. A. (1984). 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