Currently in Pakistan, the agricultural sector contributes up to 18.9% of the gross domestic product. As a result of modern science and technology development, the source of income for rural households is changing, and nonfarm income has become the main source. This study investigates the effects of nonfarm income on agricultural productivity in rural Pakistan. The current research data has been collected from the Pakistan Social and Living Standards Measurement Survey (PSLM) 2017-2018, a sample of rural and urban areas designed by Pakistan's Federal Bureau of Statistics. In this study, Heckman's two-step procedure is used to tackle the problems of endogeneity and selection bias. The first phase, probit regression, indicates that the accessibility of banks, motorable roads, forest, telecommunication substructure, montane grasslands, and shrublands zone affects nonfarm income. On the other hand, the second stage, ordinary least squares regression, found a negative impact of nonfarm income on per capita farm income. Furthermore, results reveal that nonfarm household income has a significant positive effect on agricultural productivity.