Abstract: The pricing role of idiosyncratic risk has remained debatable to date, In this paper, we applied an innovative method of dual-predictor regression models to test for the predictive power of idiosyncratic risk in major African stock markets, we find that even though the conventional measure of aggregate idiosyncratic risk exhibits some predictive power for future stock returns, the dual-predictor method, which is developed to reduce the noise effect and is subsequently applied to the US stock market in Ruan, Sun, and Xu (2016), can substantially improve the predictive power of idiosyncratic risk in all of the five major African stock markets, consistent with the effect of the dual-predictor on noise reduction. We conclude that innovative approaches help to improve the predictive power of idiosyncratic risk and just as is the case in the US markets, the same argument of noise reduction through innovation also holds in major African stock markets.