Predicting the onset of psychosis is crucial for early intervention and improved outcomes. This review examines the current state of prediction models based on clinical, neurocognitive, and linguistic factors. Clinical predictors, including sociodemographic characteristics, family history, and subthreshold psychotic symptoms, have shown promise in identifying people at risk, and some models achieve concordance indices of 0.79-0.80 in external validation. Neurocognitive evaluation, particularly of verbal learning, processing speed, and attention/vigilance, has emerged as a cost-effective predictor, although the effect sizes remain modest. Recent advances in natural language processing have enabled automated analysis of speech patterns, with reduced semantic coherence and specific linguistic features predicting the transition to psychosis with precisions of up to 83%. Although these approa...