An auxiliary determination device for evaluating whether a transcranial magnetic stimulation (TMS) is effective for a patient with depression is provided. The device includes a feature extraction unit and a machine learning unit electrically connected thereto. In an interpretation mode, the feature extraction unit extracts a feature value from electroencephalography signals of the patient, and at least a classifier of the machine learning unit determines the efficacy of TMS for the patient according to the feature value of the electroencephalography signals. The electroencephalography signals are electroencephalography signals of the patient after being driven by a cognitive operation or a difference between electroencephalography signals before and after being driven by the cognitive operation, and the feature value is a linear or non-linear feature value. The auxiliary determination device of the invention can pre-evaluate the efficacy of TMS for the patient for avoiding ineffective treatment and unnecessary medical expense.