A method for generating prediction information, applied to a first backend server, comprising: generating, based on first user characteristic information of a target user stored on the first backend server, anonymous user information of the target user; sending (202, 302) the anonymous user information to a second backend server to enable the second backend server to generate prediction information (107, 506, 606) based on the anonymous user information and second user characteristic information of the target user stored on the second backend server, wherein the first user characteristic information cannot be deciphered through the anonymous user information; wherein the anonymous user information is obtained based on a first prediction sub-model (1051, 5041, 6042) in the first backend server, the prediction information (107, 506, 606) is obtained based on a second prediction sub-model (1052, 5042, 6041) in the second backend server, the first prediction sub-model (1051, 5041, 6042) and the second prediction sub-model (1052, 5042, 6041) are obtained by dividing a prediction model; wherein the generating, based on the first user characteristic information of the target user, the anonymous user information of the target user comprises: inputting the first user characteristic information into the first prediction sub-model (1051, 5041, 6042) to obtain a first user characteristic embedding vector; splicing the first user characteristic embedding vector and a context vector to obtain a splicing vector; multiplying the splicing vector and a parameter matrix of the first prediction sub-model (1051, 5041, 6042) to obtain the anonymous user information of the target user. generating, based on first user characteristic information of a target user stored on the first backend server, anonymous user information of the target user; sending (202, 302) the anonymous user information to a second backend server to enable the second backend server to generate prediction information (107, 506, 606) based on the anonymous user information and second user characteristic information of the target user stored on the second backend server, wherein the first user characteristic information cannot be deciphered through the anonymous user information; wherein the anonymous user information is obtained based on a first prediction sub-model (1051, 5041, 6042) in the first backend server, the prediction information (107, 506, 606) is obtained based on a second prediction sub-model (1052, 5042, 6041) in the second backend server, the first prediction sub-model (1051, 5041, 6042) and the second prediction sub-model (1052, 5042, 6041) are obtained by dividing a prediction model; wherein the generating, based on the first user characteristic information of the target user, the anonymous user information of the target user comprises: inputting the first user characteristic information into the first prediction sub-model (1051, 5041, 6042) to obtain a first user characteristic embedding vector; splicing the first user characteristic embedding vector and a context vector to obtain a splicing vector; multiplying the splicing vector and a parameter matrix of the first prediction sub-model (1051, 5041, 6042) to obtain the anonymous user information of the target user. inputting the first user characteristic information into the first prediction sub-model (1051, 5041, 6042) to obtain a first user characteristic embedding vector; splicing the first user characteristic embedding vector and a context vector to obtain a splicing vector; multiplying the splicing vector and a parameter matrix of the first prediction sub-model (1051, 5041, 6042) to obtain the anonymous user information of the target user.