As Artificial Intelligence (AI) permeates psychiatric evaluation, predictive diagnostic models raise critical neuro-ethical concerns regarding patient autonomy, privacy, and algorithmic determinism. This comprehensive article investigates the societal and psychological implications of relying on machine-learning algorithms to forecast mental health crises. By analysing current technological frameworks, historical precedents of psychiatric labelling, and data governance, the study evaluates how automated diagnostics may unintentionally marginalize vulnerable populations. Furthermore, it proposes a multidimensional ethical matrix designed to safeguard humancentric care while embracing technological advancement. The findings suggest that while AI offers unprecedented scalability in early intervention, it fundamentally risks reducing complex human emotions to quantifiable metrics. Ultimately, this research calls for a mandatory ethical oversight framework in digital mental health, ensuring that algorithms serve as supplementary clinical tools rather than autonomous arbiters of psychiatric health.