Smallholder farmers’ preferences for participation in contract farming may take the form of proportional data – whereby farmers only sell some proportions or fractions of output to contractors. We analyze determinants for preferences for zero (potential corner solution) and proportional amounts of milk that farmers sell through contract farming using dairy farmers’ data from Zambia. Bayesian linear, linear probability, and hurdle models are compared with a Bayesian zero-one-inflated beta regression. Monte Carlo simulations show that alternative models are biased. Meanwhile, empirical findings suggest gender and marital status of the household head, household size, and delayed payment significantly drive preferences for proportional milk sales in contract farming. Additionally, household size, experience selling through milk collection centers, total livestock units, access to dairy marketing information, and buyer's milk price among others, tend to affect zero-inflated outcomes. We recommend a Bayesian zero-one-inflated beta regression model for proportional data and also provide strategies to overcome farmer-engagement barriers in contract farming.