Bearing is among the most widely used components in rotating machinery. Its failure can cause serious economic losses or even disasters. However, the fault-induced impulses are weak especially for the early failure. As to the bearing fault diagnosis, a novel bearing diagnosis method based on scale-varying fractional-order stochastic resonance (SFrSR) is proposed. Signal-to-noise ratio of the SFrSR output is regarded as the criterion for evaluating the stochastic resonance (SR) output. In the proposed method, by selecting the proper parameters (integration step [Formula: see text], amplitude gain [Formula: see text] and fractional-order [Formula: see text]) of SFrSR, the weak fault-induced impulses, the noise and the potential can be matched with each other. An optimal fractional-order dynamic system can be generated. To verify the proposed SFrSR, numerical tests and application verification are conducted in comparison with the traditional scale-varying first-order SR (SFiSR). The results prove that the parameters [Formula: see text] and [Formula: see text] affect the SFrSR effect seriously and the proposed SFrSR can enhance the weak signal while suppressing the noise. The SFrSR is more effective for bearing fault diagnosis than SFiSR.