Background: Depression represents one of the leading causes of disability due to illness worldwide. Previous studies have demonstrated the significant heterogeneity of the diagnosis of depression, making it necessary to develop new diagnostic approaches. Network analysis is a perspective that considers symptoms as constituents of the psychiatric disorder itself. The objective was to determine the structure of depressive symptoms using the CES-D and ZDS depression scales. Methods: Cross-sectional study of secondary analysis of 194 patients using the CES-D and ZDS scales. Correlation matrices and regularised partial correlation networks were constructed from the database. Centrality measures were estimated, and a network stability analysis was performed. Results: On the CES-D scale, the most central item was “Sad”; while on the ZDS scale, the most central items were “Sad” and “Live”. On the CES-D scale, the connection between “Enjoy” and “Happy” was the strongest. On the ZDS scale, the strongest connection was between the items “Live” with “Useful”. The item “Morning” was the least connected on the ZDS. Conclusions: The most central symptom from the CES-D scale was sadness, while from the ZDS scale, was sadness and anhedonia.