A cooperative mutual fund is an important cooperative-based financing option for farmers in China. As its farmer-borrowers often do not have formal records, a lending decision generally relies heavily on subjective evaluation. This experienced-based judgment has been relatively accurate but is less useful as seasoned loan officers retire or as growth necessitates hiring novice lenders. A credit scoring model was developed to capture the knowledge of experienced loan officers and thereby assist those more novice. The model evaluates a farmer’s credit standing based on family background, willingness to repay, repayment capacity, and relationships. The analytic hierarchy process is used to determine factor weighting and the model is empirically tested. The model’s predictive accuracy is high, with most error attributed to core indicators in the model that have strong veto power. Therefore, we suggest supplementing the credit scoring model with a crucial indicator negation system.