Random slopes are used in mixed-effects models to allow the relationship between predictors and response variables to vary across groups, capturing individual differences in how predictors affect outcomes. This flexibility improves model accuracy and generalizability by accounting for heterogeneity in data, which fixed-effects models might overlook.