This study aimed to evaluate the impact of face masks used for COVID-19 prevention on emotion recognition in facial expressions. Seventy-two (72) adult participants (48 females, 24 males) attempted to correctly identify different emotions displayed by a female and a male actor’s facial expressions. Simulated emotions included neutrality, happiness, surprise, disgust, sadness, fear, and anger at two levels of intensity, with or without wearing a surgical mask. Accuracy rates of facial expression recognition and response times were collected. The GLM analysis for accuracy revealed a main effect of emotions (F(5,350)=57.47, P<.001) and face masks (without>with) (F(1,70)=338.95, P<.001), as well as a three-way interaction between emotions, masks, and actors (F(5,350)=9.69, P<.001). Disgust was the least recognized emotion, followed by sadness, while happiness, anger and surprise were the easiest to identify. The analysis of response times suggested that, when partially covered by a mask, facial expressions can be more ambiguous and difficult to read, and a larger amount of time was required to provide a response. In line with results on accuracy, sadness was generally the most difficult emotion to identify. Male and female participants had similar response times. Globally, these results show that wearing masks can significantly reduce the ability to detect emotions in facial expressions. However, when emotions are expressed at higher intensity levels, this effect may be mitigated.