This study explores the automatic detection of suicidal ideation in social media posts, specifically on Reddit. It focuses on using deep learning and machine learning approaches to recognize and classify suicidal content. The research employs a combined LSTM-CNN model and compares its performance with other classification models. Results indicate that the LSTM-CNN model, utilizing word embedding techniques, achieves superior classification results for detecting suicide ideation. The findings demonstrate the effectiveness of deep learning architectures in assessing suicide risk in text classification tasks.