The present study analyzes the extra insights that option pricing models may achieve when uncertainty about parameters is modeled through fuzzy numbers. Specifically, we consider the Heston stochastic volatility model, which assumes that stock price changes and their instantaneous variance evolve as a bivariate, possibly correlated, diffusive process. The original Heston model provides a quasi-closed formula for the pricing of several derivative products such as European options. By applying the fuzzy extension principle, we generalize the model to the case of fuzzy parameters; given their shape we are able to derive the membership of the fuzzy price of a European option. Finally, to understand the extent to which our approach might...