We explored sociodemographic and illness/need associations with both recent mental healthcare utilization intensity and self-reported behavioral intentions to seek treatment. Data were examined from a community sample of 201 participants presenting for medical appointments at a Midwestern U.S. primary care clinic, in a cross-sectional survey study. Using non-linear regression analyses accounting for the excess of zero values in treatment visit counts, we found that both sociodemographic and illness/need models were significantly predictive of both recent treatment utilization intensity and intentions to seek treatment. Need models added substantial variance in prediction, above and beyond sociodemographic models. Variables with the greatest predictive role in explaining past treatment utilization intensity were greater depression severity, perceived need for treatment, older age, and lower income. Robust variables in predicting intentions to seek treatment were greater depression severity, perceived need for treatment, and more positive treatment attitudes. This study extends research findings on mental health treatment utilization, specifically addressing medical patients and using statistical methods appropriate to examining treatment visit counts, and demonstrates the importance of both objective and subjective illness/need variables in predicting recent service use intensity and intended future utilization.