Abstract: Disclosed is a privacy-preserving neural network prediction system in the technical field of information security. The system includes a client, a server and a third party device. Off-line, the client, the server and the third party complete model parameter sharing through negotiation. Online, the client sends/shares input data to the server. The client and the server use a secure calculating protocol to jointly execute neural network prediction with privacy preservation. The server returns an obtained prediction result to the client, and the client reconstructs the prediction result. Only one round of communication interaction is required, and the amount of communication overhead is reduced, so that the communication efficiency significantly improves. The calculations in the present system may be based on a ring, rather than a domain. The present system also (re)customizes the offline protocol, which improves the offline efficiency and requires only a lightweight secret sharing operation.