This project investigates how mental health conditions affect the ability to recognize emotions from facial expressions. Using a publicly available dataset of over 570 individuals with various psychiatric disorders including anxiety, depression, insomnia, and mania we trained machine learning models to predict emotion recognition patterns. By analyzing the influence of psychological profiles on the accuracy and certainty of emotion predictions, the study aims to better understand how mental illnesses alter emotional perception and to identify which emotions are most affected.