This study uses probit model to identify determinants of food insecurity among rural households in developing countries. The model used in this study, that allowed us to estimate coefficient and marginal effect for each independent variable vis-à-vis dependent variable, guarantees large applications among food security actors and policymakers to find out factors that significantly explain food insecurity and the level of their predictability. The ability of the model used to correctly classify food insecure and food secure households is good for the overall model and for households headed by males while it is fair for households headed by females. The empirical results show that rural households are more exposed to food insecurity than urban households. Gender disaggregation by the head of households shows that among food insecure rural households, the majority of them are headed by females. It also shows that the mean and median of predicted probability of becoming food insecure among rural households headed by males and females is 0.21 and 0.28 for mean and 0.15 and 0.24 for median respectively. This indicates that households headed by females are more likely exposed to food insecurity than those headed by males. However, as the majority of rural households in developing countries depend on agriculture, this study found that it is worthwhile for developing countries to adopt new agricultural technologies to urgently increase productivity and to implement and facilitate programs supporting rural households pathways to increase households’ livelihood capacities.