© Copyright 2015 Physicians Postgraduate Press, Inc. Background: Previously, a biomarker panel was developed for use as an aid to major depressive disorder (MDD) diagnosis; it consisted of 9 biomarkers associated with the neurotrophic, metabolic, inflammatory, and hypothalamicpituitary- adrenal axis pathways. This panel and associated algorithm produced good clinical sensitivity and specificity (92% and 81%, respectively) in differentiating MDD patients from individuals without MDD. To further validate the panel, we performed a prospective study using a larger set of new prospectively acquired MDD patients and a similarly collected population of nondepressed subjects. The addition of gender and body mass index (BMI) effects to the algorithm was also evaluated. Method: Blood samples were obtained from MDD patients (n = 68) clinically evaluated at multiple sites in 2011 and 2012 using standard psychiatric assessment tools and structured clinical interviews according to DSM-IV criteria. Blood samples (n = 86) from nondepressed subjects were obtained as controls. MDD and nondepressed samples were randomized into independent training (n = 102) and validation sets (n = 52). Analytes in sera were quantified by immunoassay. Results: Training set biomarker data were used to develop a logistic regression model that included gender and BMI in a manner that allowed for their interaction with the biochemical analytes. For the training set, the sensitivity and specificity of the test (with 95% CI) were 93% (0.80-0.98) and 95% (0.85-0.99), respectively. This method (designated the MDDScore) was then applied to the independent validation set and had a sensitivity and specificity of 96% (0.77-0.98) and 86% (0.66-0.95), respectively. The overall accuracy for the training set was 94%; the validation set accuracy was 91%. Conclusion: Examination of a randomized independent set of samples confirms the ability of the previously established biomarker panel to identify persons with MDD; the accuracy was over 90%. The improved model that adds gender and BMI to the previously established panel of 9 biomarkers is robust and simple; it provides the most rigorously tested, objective diagnostic test for MDD to date.