Abstract: A machine learning model training method performed by a computer device acting as an active-party device is provided. The method includes: coding and encrypting a first object feature in the sample pairs provided by the active-party device using an active-party coding model to obtain an active-party first encrypted coding result; acquiring N passive-party first encrypted coding results correspondingly sent by N passive-party devices in combination with a second object feature in the sample pairs; splicing the active-party first encrypted coding result and the N passive-party first encrypted coding results to obtain a first spliced encrypted coding result, and applying the first spliced encrypted coding result to a first prediction model to obtain a first prediction probability; and causing an update of parameters of the different models based on a first difference between the first prediction probability and a first prediction task label of the sample pairs.