Rapid and accurate three-dimensional positioning of particles has important applications in life science, material science, industrial detection, and other fields. The traditional particle location methods cannot meet the requirement of fast and accurate because of heavy computation. A new 3D particle locating method based on phase mask is proposed. Fienup optimization algorithm was used to design the phase mask on the spectrum plane of a 4f imaging system, and a series of point spread functions were obtained for different depth of point light sources. By training the neural network based on the particle positions and generated images, the target particle can be located in 3D space with high precision by a single measurement within the axial range of 8 μm. Numerical simulation results of two sets of design show that the proposed method can quickly and efficiently complete the three-dimensional locating of sparse particles, and may have important applications in the locating of cell particles.