The purpose of this study was to explore the relationship between patient-provider language concordance and behavioral health help seeking behaviors among the AAPI population. Guided by Andersen’s Behavioral Model of Health Service Use, the current study examines the rate of behavioral health service utilization among groups with various levels of patient-provider language concordance as well as the significance of time between evaluated need of behavioral health service and service utilization. A secondary data analysis using electronic health records from a federally qualified health center in California was used to explore the research question. Patient Health Questionnaire 2-Item Scale (PHQ-2) depression pre-screening scores were collected during primary care encounters and a positive score was used to assess evaluated need of behavioral health services. A Cox Regression model was used to analyze the event (behavioral health service use) and time (time between primary care and behavioral health appointment) compared to a reference group of patients with no language barriers. Of all patients in the analytic data set (n=846), 131 (15.5%) attended behavioral health services following a primary care appointment. In the multivariable model, compared to patients with no language barriers, AAPI with language barriers and availability of a language concordant behavioral health provider had a hazard ratio of 1.101; AAPI with language barriers and availability of a language concordant behavioral and primary care providers had a hazard ratio of 1.121. However, these results were not significant. This indicates that there is little to no difference in help seeking behaviors when compared to patients with no language barriers. AAPI patients with language barriers and no language match with providers were 17% less likely to attend behavioral health services following a primary care referral; however, the results were not statistically significant. Future research efforts should focus on examining variations in behavioral health service use among disaggregated AAPI ethnic subgroups considering each diverse subgroup is rich with cultural context that becomes lost with aggregated data. A mixed methods approach may be appropriate and special attention should be given to predisposing factors related to cultural influences, such as perception of mental health, stigma, and acculturation levels.