The aim of the present study was to assess the Indian Ocean yellowfin tuna () using a Bayesian biomass dynamic model and to analyze the impacts of two standardized longline CPUE (catch per unit effort) series from Japan and Taiwan and the prior distributions of intrinsic rate of increase () on the results of the assessments. (1) The models fit the standardized CPUE from Japan better than that from Taiwan, and the results indicated that the stock was overfished and subject to overfishing when the standardized CPUE from Japan was singly used in the models. The opposite might be achieved using the standardized CPUE from Taiwan. Furthermore, when both standardized CPUEs were used, the weighting of the model-estimated Japan standardized CPUE was greater than that of the Taiwan standardized CPUE, and the results were similar for models where only the Japan standardized CPUE was used. (2) If uninformative prior was assigned to was likely to be underestimated, and the carrying capacity (, the estimates of seemed more reasonable. Because there is often a strong negative correlation between in biomass dynamics models, it is difficult to correctly estimate simultaneously, especially under data-poor situations. However, by using informative priors, estimates of parameters of biomass dynamics models can be improved. (3) Deviance information criterion (DIC) and mean square error (MSE) were used to evaluate model fitness, and model S8 was selected as the best model for assessing stock status. According to model S8, Indian ocean yellowfin tuna are overfished and subject to overfishing, which was identical to the results based on Stock Synthesis.