Using smartphone data, this study assessed depression symptoms in 99 participants, including controls and those with various depressive disorders. 32 behavioral markers were employed to predict depression symptoms. These markers effectively classified depression severity and monitored changes, demonstrating high accuracy in detecting depressed individuals and observing shifts in depression states. This approach shows promise as a supplementary tool to traditional methods, offering real-time, objective insights into depression through digital behavioral markers.