The accelerating convergence of climate change, environmental degradation, and rising pollution levels presents profound implications for adolescent mental health, particularly within rapidly urbanizing and resource-strained regions. Traditional public health frameworks often assess these risks in isolation, overlooking the interconnected ecological, human, and animal health dimensions emphasized by the One Health approach. At the same time, advances in artificial intelligence (AI) including multimodal sensing, deep learning, and predictive environmental analytics now offer unprecedented opportunities to identify, model, and mitigate climate- and pollution-related mental health vulnerabilities among adolescents. This study presents a forward-looking synthesis of AI-enhanced environmental health modeling, highlighting how integrated systems can detect early psychosocial stressors linked to temperature extremes, poor air quality, toxic exposures, and disrupted ecological conditions. The paper outlines how machine learning models can incorporate satellite data, environmental sensor streams, electronic health records, and behavioural indicators to generate risk predictions with high spatial and temporal resolution. It also explores how these models can map environmental injustice patterns, revealing how marginalized adolescent populations experience disproportionate exposure to environmental harms and associated mental health burdens. As the focus narrows, the analysis demonstrates how hybrid One Health–AI architectures can enable early-warning systems that identify adolescents at elevated risk of anxiety, depression, emotional dysregulation, and cognitive impairment triggered or intensified by climate-induced stressors. The article further discusses ethical considerations, including data privacy, transparency, algorithmic bias, and the need for culturally competent implementation within schools, community health structures, and digital mental health platforms. Ultimately, this work argues that AI-augmented One Health models represent a transformative pathway for safeguarding adolescent mental well-being amid escalating climate volatility and environmental pollution. Strengthening these systems will be essential for building resilient public health responses capable of protecting the next generation in an era of accelerating ecological change.