Fuzzy logic systems based on If-en rules are widely used for modelling of the systems characterizing imprecise and uncertain information. ese systems are basically based on type-1 fuzzy sets and allow handling the uncertain and imprecise information to some degree in the developed models. Zadeh extended the concept of fuzzy sets and proposed Z-number characterized by two components, constraint and reliability parameters, which are an ordered pair of fuzzy numbers. Here, the rst component is used to represent uncertain information, and the second component is used to evaluate the reliability or the con dence in truth. Znumber is an e ective approach to solving uncertain problems. In this paper, Z-number-based fuzzy system is proposed for estimation of food security risk level. To construct fuzzy If-en rules, the basic parameters cereal yield, cereal production, and economic growth a ecting food security are selected, and the relationship between these input parameters and risk level are determined through If-en fuzzy rules. e fuzzy interpolative reasoning is proposed for construction of inference mechanism of a Z-number-based fuzzy system. e designed system is tested using Turkey cereal data for assessing food security risk level and prediction periods of the food supply.