Objective To explore the effect of early changes of composite indicators of image cognition-based psychometric techniques in the treatment of acute depression. Methods From January 2019 to December 2020， a total of 135 patients with depression who were treated in the outpatient clinic of Beijing Anding Hospital Affiliated to Capital Medical University were selected. All patients received antidepressants and assessed for treatment efficacy by Hamilton Depression Scale-17 （HAMD-17） at baseline and the end of 8 weeks. According to the HAMD-17 reduction rate， patients were divided into treatment effective group and treatment ineffective group. The psychological assessment based on image cognition was completed at baseline and the end of 2 weeks. Eye movement trajectory and reaction time were obtained by assessment. The features that could be used for analysis were extracted through data pre-processing， and a prediction model was constructed using multifactorial Logistic regression analysis. It was evaluated that the prediction ability of composite indexes on antidepressant treatment in patients with depression after 8 weeks in receiver operating characteristic （ROC） curve. Results The composite index includes cognitive speed PN and cognitive speed PP. Multifactorial Logistic regression analysis showed that the area under the ROC curve for the composite index to predict effective treatment at the end of week 8 in depressed patients was 0.628， with a sensitivity of 65.9% and a specificity of 55.8%. Conclusions The composite index of psychological assessment technology based on image cognition can be used to predict the treatment outcome of patients with depression in the acute phase， but it still needs to be verified by large-scale independent samples.