Machine learning findings suggest Eurocentric (aka White/European) faces structurally resemble anger more than Afrocentric (aka Black/African) faces (e.g., Albohn, 2020; Zebrowitz et al., 2010); however, Afrocentric faces are typically associated with anger more so than Eurocentric faces (e.g., Hugenberg & Bodenhausen, 2003, 2004). Here, we further examine counter-stereotypic associations between Eurocentric faces and anger, and Afrocentric faces and fear. In Study 1, using a computer vision algorithm, we demonstrate that neutral European American faces structurally resemble anger more and fear less than do African American faces. In Study 2, we then found that anger- and fear-resembling facial appearance influences perceived racial prototypicality in this same counter-stereotypic manner. In Study 3, we likewise found that imagined European American versus African American faces were rated counter-stereotypically (i.e., more like anger than fear) on key emotion-related facial characteristics (i.e., size of eyes, size of mouth, overall angularity of features). Finally in Study 4, we again found counter-stereotypic differences, this time in processing fluency, such that angry Eurocentric versus Afrocentric faces and fearful Afrocentric versus Eurocentric faces were categorized more accurately and quickly. Only in Study 5, using race-ambiguous interior facial cues coupled with Afrocentric versus Eurocentric hairstyles and skin tone, did we find the stereotypical effects commonly reported in the literature. These findings are consistent with the conclusion that the “angry Black” association in face perception is socially constructed in that structural cues considered prototypical of African American appearance conflict with common race-emotion stereotypes.