Metal pollutants have become increasingly diverse. Therefore, managing the ecological risks associated with these elements in soil is urgently required. However, determining the soil ecological risk thresholds of elements through routine toxicological tests is time-consuming and laborious, establishing prediction models is vital to risk management. Accordingly, this study aimed to predict the element toxicity to soil organisms by collecting the toxicological data of eight elements to soil organisms at 18 European and 17 Chinese sites through literature and toxicology databases, using the quantitative ion character-activity relationship (s-QICAR) model. Firstly, the toxicity values (logEC10) of eight elements to five biological species and three microbial processes were obtained through clustering and soil normalization methods in three typical soil scenarios. Correlation analysis revealed that for different species and microbial processes, there are three to six physicochemical properties of elements related to their toxicity, among which, the covalent radius of the element was the best significantly correlated with logEC10 of all organisms (R2 = 0.77–0.95). Based on this, the s-QICAR model was established and used to predict the logEC10 of Sc, Ti, V, Cr, Co, Ni, Cu, and Zn to eight organisms. Furthermore, along with the species sensitivity distribution curve, the HC5 values (i.e., 95% species protection level) for the above eight elements were calculated. Following correction, the predicted no-effect concentrations of these elements ranging from 9 to 189 mg/kg, and the ecological risk threshold map has been produced. In summary, we present a new method to quantify the ecological risk of metal-induced pollution in European soils without routine toxic measurements, and provide important insights into soil pollution risk assessment and management.