Experiments in multiphase flows are often limited in their ability to simultaneously obtain velocity measurements in different phases. At the same time, flow reconstruction from phase-limited measurements is a challenging problem due to the substantially different velocity statistics across the phases. We address this problem for buoyancy-driven bubbly flows in the pseudo-turbulence regime by using a guided diffusion model. We train the model using two-dimensional slices of the velocity field extracted from fully resolved three-dimensional direct numerical simulations. The model generates physically realistic velocity fields both unconditionally and when conditioned on the surrounding liquid flow. The reconstructed bubble-phase velocity field accurately reproduces key statistical features of the flow. We further show that a simple patching procedure for adjacent two-dimensional slices enables a reasonable reconstruction of the three-dimensional flow inside a bubble. These results establish the potential of diffusion models to serve as generative priors for three-dimensional turbulent multiphase flows, opening a route toward the reconstruction of unobserved or experimentally inaccessible velocity fields from sparse, partial, or phase-limited measurements.