This paper proposes an alternative approach to estimate parameters and evaluate the quanto option with stock liquidity under Bayesian framework. First, we derive an explicit expression of the quanto option price with liquidity-adjustment in an alternative way. Then, an applicable likelihood is proposed to conduct posterior inference on model parameters based on the joint distribution of underlying stock price dynamics and the exchange rate process, which provides a new perspective to estimate the correlation coefficient. Moreover, the statistical inference on the quanto option price is conducted by the posterior distribution and numerical algorithm. The proposed method considers the impact of parameter uncertainty on option prices, particularly the correlation coefficient randomness. Finally, the numerical analysis is performed for examining the effectiveness of the proposed method in terms of estimating parameters and pricing quanto options. Empirical results indicate that the proposed method is feasible in pricing and predicting quanto option with liquidity-adjustment.