Specific alterations in exosomes and their characteristics may serve as potential biomarkers for schizophrenia. By applying statistical methods, it is possible to determine the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of exosome-based diagnostic tests in patients with schizophrenia. This study aimed to analyze the diagnostic performance of exosome-based methods in identifying schizophrenia, based on sensitivity and specificity parameters, and to assess the reliability and clinical significance of these approaches. A systematic search was conducted using the PubMed, MEDLINE, Scopus, and Web of Science databases. Inclusion criteria comprised English-language publications from 2019 to 2025 that reported statistical measures of sensitivity and specificity for exosome-based tests in schizophrenia, including control groups. Out of 21 sources published between 2014 and 2025, 9 studies met the inclusion criteria. Online statistical calculators were employed to evaluate the reliability of exosome-based diagnostic methods. Statistical analysis predicted that 80% of patients with a positive test result truly have schizophrenia, while 77.039% of individuals with a negative test result were correctly identified as healthy. The area under the ROC curve (AUC) was 0.6781, indicating that while the model is not ideal, it still demonstrates moderate discriminatory ability, distinguishing between schizophrenia patients and healthy individuals with 67.8% accuracy. Exosome-based tests hold potential for screening, prognosis, and disease monitoring in schizophrenia. Although current diagnostic accuracy is moderate, these findings support further investigation and development of exosome-based biomarkers in clinical psychiatry.