Depression, the leading cause of global disability and a major suicide factor, impacts language usage in written text. This study examines Reddit posts to detect depression indicators among users using Natural Language Processing (NLP) and machine learning. A lexicon of terms common among depressed users was identified. The proposed method achieved significant performance accuracy, with the best single feature being bigram with a Support Vector Machine (SVM) classifier, achieving 80% accuracy and 0.80 F1 scores. The combined features (LIWC+LDA+bigram) with a Multilayer Perceptron (MLP) classifier reached 91% accuracy and 0.93 F1 scores, demonstrating that proper feature selection and combinations enhance detection performance.