The invention discloses a physiological information-based depressive disorder evaluation system, which comprises an information acquisition module, a signal processing module, a parameter calculating module, a characteristic selecting module, a machine learning module and a result output module. The invention further discloses a depressive disorder evaluation method based on multiple pieces of physiological information, which comprises the following steps: 1, processing one or more than one signal of an electrocardiosignal, a pulse wave signal, an electroencephalographic signal, a galvanic skin response signal, an electrogastrogram signal, an electromyographic signal, an electrooculogram signal, a polysomnogram signal and a temperature signal, and calculating signal parameters; 2, carrying out normalization on the obtained signal parameters, and carrying out characteristic selection on a parameter set consisting of the signal parameters subjected to the normalization, so as to obtain a characteristic parameter set; 3, carrying out machine learning on the characteristic parameter set, and establishing a depressive disorder evaluation mathematic model according to the relationship between the characteristic parameter set and the levels of the depressive disorder, and evaluating the levels of the depressive disorder. The physiological information-based depressive disorder evaluation system and method have the advantages that subjectivity of scale evaluation and the like can be avoided.