Soil is the main medium for plants， animals， and humans to obtain the selenium element required for growth and development. Rapid economic development has caused serious soil heavy metal pollution， threatening soil environment and human health. Therefore， predicting the spatial distribution of soil selenium elements and delineating "clean and selenium-rich land" with low heavy metal pollution risk can provide a reference for the healthy development of agriculture and industry. A total of 212 soil samples were collected in part of Zibo City for selenium and heavy metals testing. The integrated nested Laplace approximation-stochastic partial differential equation （INLA-SPDE） method was used to integrate five environmental covariates， including distance to roads and factories， soil type， rainfall， and soil particle size， to predict the spatial distribution of soil selenium elements. Combined with the pollution thresholds determined by the finite mixture distribution model （FMDM）， the selenium-rich areas were optimized. The results show that： ① The average selenium content in the study area was 0.34 mg·kg-1， higher than the background value of selenium in Shandong soil and the national average. ② The INLA-SPDE method prediction results showed that the spatial variation of soil selenium content was related to natural factors and human activities； the selenium-rich land was concentrated in the middle of the study area， with an area of 423.49 km2. The distribution of spatial prediction standard deviation showed that the sampling density was high， and the prediction uncertainty was small. ③ According to the pollution threshold provided by the FMDM model， the areas with selenium-rich land lower than the medium pollution threshold and high pollution threshold were 2.22 km2 and 291.81 km2， respectively. The optimization of selenium-rich land can provide a reference for sustainable development， soil environment control， and human health protection.