A fish navigating between two points in space is required to orient in three dimensions, unlike surface-bound animals that only need to deal with two. A sense of depth would therefore be extremely useful for fish to localize position, for example, when navigating to feeding grounds at a specific vertical position in the water column. Hydrostatic pressure represents a global, reliable, quantifiable cue in the vertical axis that could be used to inform depth. From a theoretical perspective, we have shown that fish could use their swim bladder to infer depth by detecting changes in hydrostatic pressure during ascent and descent, however, this has never been tested empirically. Here we use the Mexican Banded Tetra (Astyanax fasciatus) to test whether fish are indeed able to sense depth by using hydrostatic pressure alone. Using an operant learning paradigm, we trained A. fasciatus to associate a specific depth with a food reward. By changing a known quantity of water during testing we could predict the shift in vertical position in which the fish searches for food and hence test whether A. fasciatus can use hydrostatic pressure alone to ascertain depth.