Heavy metal(loid)s (HMs) in soils near mining sites often cause serious environmental and health issues. Accurately assessing soil HM risks and identifying priority pollutants are crucial for improving risk control efficiency with limited management costs and resources. Traditional deterministic assessments may yield biased results due to the imprecision and ambiguity of environmental data and assessment processes. To compensate for the deficiencies of deterministic assessment, a comprehensive probabilistic-fuzzy model was developed based on fuzzy theory, probability methods, the soil contamination risk (SCR) index, and a human health risk (HR) assessment framework. According to this model, the soil HM risk status in a typical mining area in China was evaluated. The results indicated that Cd and Cu significantly violated the relevant environmental guidelines and were considered priority metals for environmental risk (ER). Notably, Cd’s hazard predominantly manifested in a solid potential ecological risk (PER), whereas Cu’s environmental impact primarily manifested as a soil contamination risk (SCR). From the perspective of HR, soil HMs already pose a considerable threat to human health, with children facing greater HRs than adults. As was identified as a priority element for HRs, with carcinogenic and non-carcinogenic risks reaching unacceptable levels. Regarding general risk (GR), Cd and Cu ranked in the first gradient and As in the second gradient. Overall, the accumulation of soil HMs—especially Cd, Cu, and As—in the study area has posed a significant threat to the ecosystem and human health. The risks of other HMs (Pb, Zn, Cr, and Ni) are relatively low, but the superimposed risks of multiple HMs should not be ignored. The probabilistic–fuzzy model reduces the uncertainty of risk assessment, and the model integrates the environmental and health risks of HMs, providing more comprehensive risk information. The assessment results can serve as a reference for managers to develop targeted control strategies.