To perform sustainable land use management, it is essential to predict accurately spatial distribution of soil fertility quality and identify problem areas in soil fertility quality. Based on the soil fertility quality data of a total of 99 samples of topsoil (0~20 cm) from Yucheng City, the sequential Gaussian simulation (SGS) method was applied to a conditional stochastic simulation in this paper to quantitatively assess the uncertainty of spatial distribution prediction of soil fertility quality and identify problem areas in soil fertility quality. Results show that the southwestern and the central parts of Yucheng City are higher than the northern part, the northwestern and the southeastern parts in soil fertility quality. By making use of the relationship between soil fertility and crop yield, the threshold value for identifying problem areas in soil fertility quality is determined to be 0.55. The soil quality indices of most parts of the city are beyond the value. Using this cutoff value and the spatial uncertainty assessment, only a total of 2 494 hm² of land is identified as problem area. The main limiting factors are soil texture and low soil total phosphorus content in the northern part of the study area, soil salinization in the northwestern part, and low soil nutrient availability nutrient, soil salinization, poor soil texture and low soil total nitrogen content.