This study proposes a fuzzy-probabilistic modelling approach for groundwater contamination risk assessment (FPM-risks) regarding underground fuel storage tanks (UFST). Considering the subjective measures of hydrogeological parameters, a fuzzy inference system is proposed to assess the intrinsic vulnerability of aquifers (Y). Measurement of the UFST hazard degree (H) and natural groundwater quality (Q) is considered as a pattern framing issue, such that they were quantified by fuzzy-analytic hierarchy process (AHP) of the recognizing patterns model. Though the association among Q and the probability of using groundwater reserves (G), estimated by the Monte Carlo method, the consequences of contamination (C) were measured. Associating Y, H, and C, the basic and value-weighted risk assessment of groundwater contamination was performed in the urban zone of Belém city, Pará state, Brazil. The results showed that the majority of UFSTs concentrated in the more urbanized zone were classified by FPM-risks as high basic risk and very high value-weighted risk of groundwater contamination. Although the risk assessment should be updated regularly because of the dynamic characteristics of hazards from the USFTs, the FPM-risks was shown as a tool to be considered for managing groundwater resources, as these models overcome subjectivities and address uncertainties, thereby providing a higher level of accuracy than usual risk methods and possibly become a decision-making way.