<![CDATA[This study developed a predictive method using the Naïve Bayes Classifier to assess depression levels in adolescents, focusing on psychological and environmental factors. The method measures the probability of various symptom categories: emotional, physical, and cognitive symptoms. Analysis results indicate that adolescents with a combination of these symptoms have a high risk of severe depression, with the highest probability value v=0.0056. The most common symptoms in the sample include decreased energy with fatigue and reduced activity, anxiety, changes in appetite (slight decrease or increase), and unexplained aches or pains, underscoring the strong influence of psychological factors. This predictive model aids in early identification of depression levels, and the Naïve Bayes Classifier is proven effective for analyzing relationships between internal and external factors. This research can enhance mental health awareness among adolescents and parents, and educate on the negative impact of environmental factors to support early detection and prevention of mental disorders.]]>
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