Musicians usually want to express emotions with their music. In turn, their listeners want to detect these emotions, and usually they can. Research suggests that the ability to detect music-expressed emotion varies in individuals just like the ability to detect emotions conveyed through vocal expression (Mayer, Roberts, & Barsade, 2007). Differences in the ability to recognise music-expressed emotions have been linked to personality traits of the listener (Vuoskoski & Eerola, 2011). This study wants to examine which of the Big Five traits can best predict the ability to discriminate emotions in music. We used a cross-sectional sample from the longitudinal LongGold project consisting of 762 students (13.48 years, SD = 2.01 years, 69.03% female) from secondary schools (455 UK, 218 Germany). Personality was measured using the TIPI (Gosling, Rentfrow, & Swann, 2003) and emotion discrimination ability was tested with the EDT (MacGregor & Müllensiefen, 2019). Correlational analyses indicated associations between the EDT and agreeableness (r = 0.12, p < .01), openness (r = 0.19, p < .01) and conscientiousness (r = 0.11, p < .01), whereas a multiple regression showed that only openness (b = .02, p < .01) and emotional stability (b = .01, p < .05) predicted musical emotion discrimination ability. About 5% of variance was explained. A random forest regression model produced comparable results, explaining 7% of variance. The results suggest that openness is the best predictor for emotion detection in music, but that this trait explains only a small amount of variance in this ability.