Our project addresses the problem of manual flair assignment on Reddit, which can be confusing for users and unintuitive for information retrieval. By applying Machine Learning and Natural Language Processing, we developed "Flair-It," a tool that automates flaring for posts. Our main model, RoBERTa, achieved a 59% accuracy rate, outperforming simpler models like Multinomial Naive Bayes (54%), Logistic Regression (53%), and SVM Classifier (53%). This automation streamlines subreddit navigation, helping users find relevant posts more easily and reducing the likelihood of mis-flaring. Ultimately, our project enhances the user experience on Reddit, making it more accessible and user-friendly.