The invention discloses a storage device fault prediction method and system, and belongs to the technical field of computer storage. The method comprises the following steps: S1, acquiring SMART attribute data of N storage devices at different time points; S2, disordering the sequence of all the storage devices and selecting the j = 1 storage device; S3, using the SMART attribute data of the storage device at each time point as small-batch samples and input into a fault prediction model for training, and an output result is obtained; S4, dynamically adjusting the label and feedback weight of each sample according to the state of the time point tn of the storage device, the output result, the LTMIN and the LTMAX; s5, calculating the comprehensive loss Lossj of the batch; S6, selecting a next storage device, and repeating the steps S3 to S6; S5, calculating the total loss Lossfinal of all the storage devices in the period until all the storage devices are taken out; S7, judging whether Lossfinal is converged or not, if yes, obtaining a trained prediction model, entering the step S8, and otherwise, entering the step S2; and S8, inputting the current SMART attribute data of the to-be-predicted storage device into the trained prediction model to obtain a prediction result.