Abstract : Social media platforms are crucial spaces for discussing mental health issues. They can provide support systems but also act as risk factors for individuals experiencing distress. This paper proposes a system utilizing Bidirectional Encoder Representations from Transformers (BERT) to classify Reddit posts into mental health categories such as bipolar disorder, depression, anxiety, suicide, and others. The classifier is trained on posts collected from relevant subreddits, with preprocessing and feature extraction handled using NLP techniques. The results demonstrate the feasibility of using BERT-based models for classifying mental health indicators from text data. Furthermore, the paper proposes an application where social media platforms subtly adjust users’ feeds to promote positive content when signs of mental health distress are detected.