Group lending has been widely adopted in the past thirty years by many microfinance institutions as a means to mitigate information asymmetries when delivering credit to the poor. This paper proposes an empirical method to address the potential omitted-variable problem resulting from unobserved group types when modeling the repayment behavior of group members. We estimate the model using a rich dataset from a group-lending program in India. The estimation results support our model specification and show the advantages of relying on a type-varying method when analyzing the probability of default of group members. In particular, our model helps to better understand the factors driving repayment behavior, which may differ across group types, and shows a higher predictive power than standard single-agent choice models.