This study presents the design of soft sensors for estimation of bitumen froth quality in an oil sands natural froth lubricated (NFL) transportation process. One of the most important quality indexes for bitumen froth is the water content. Due to the variation in oil sands composition and the nature of multi-phase process conditions, existing hardware sensors are not reliable enough to provide on-line accurate water content measurement. Laboratory analysis result is obtained off-line with large sampling interval and irregular time delay. Therefore, it is not sufficient for real-time monitoring and control. To overcome these limitations, Bayesian information synthesis approach is proposed to fuse all the existing information to produce more reliable and more accurate real-time froth quality information. This technique has been applied in Syncrude Canada Extraction operations; both monitoring and control performance illustrate the promising perspectives of the proposed approach. (c) 2012 Canadian Society for Chemical Engineering