A method for preloading an application, being applied to a terminal device, the method comprising: acquiring current state feature information of the terminal device, when an application preloading prediction event is detected to be triggered ; inputting the current state feature information into a plurality of classification and regression tree, CART, prediction models each corresponding to an application in a preset application set , to cause each of the CART prediction models to output a probability value indicating a probability that an associated application of the CART prediction model is about to be initiated, wherein each of the CART prediction models is generated based on a usage regularity of its associated application that corresponds to historical state feature information of the terminal device; acquiring the probability values output by the plurality of CART prediction models, comprising: acquiring a probability value output from a leaf node of each CART prediction model that matches the current state feature information in each CART prediction model ; predicting a target application to be initiated according to the probability values output by the CART prediction models , comprising: selecting N probability values having the greatest values from the acquired probability values , wherein N is a positive integer greater than or equal to one; and determining applications corresponding to the selected N probability values as the target applications to be initiated ; and preloading the target applications . acquiring current state feature information of the terminal device, when an application preloading prediction event is detected to be triggered ; inputting the current state feature information into a plurality of classification and regression tree, CART, prediction models each corresponding to an application in a preset application set , to cause each of the CART prediction models to output a probability value indicating a probability that an associated application of the CART prediction model is about to be initiated, wherein each of the CART prediction models is generated based on a usage regularity of its associated application that corresponds to historical state feature information of the terminal device; acquiring the probability values output by the plurality of CART prediction models, comprising: acquiring a probability value output from a leaf node of each CART prediction model that matches the current state feature information in each CART prediction model ; predicting a target application to be initiated according to the probability values output by the CART prediction models , comprising: selecting N probability values having the greatest values from the acquired probability values , wherein N is a positive integer greater than or equal to one; and determining applications corresponding to the selected N probability values as the target applications to be initiated ; and preloading the target applications . acquiring a probability value output from a leaf node of each CART prediction model that matches the current state feature information in each CART prediction model ; predicting a target application to be initiated according to the probability values output by the CART prediction models , comprising: selecting N probability values having the greatest values from the acquired probability values , wherein N is a positive integer greater than or equal to one; and determining applications corresponding to the selected N probability values as the target applications to be initiated ; and preloading the target applications . selecting N probability values having the greatest values from the acquired probability values , wherein N is a positive integer greater than or equal to one; and determining applications corresponding to the selected N probability values as the target applications to be initiated ; and preloading the target applications . <EOS>