  Considering applications to relativistic heavy-ion collisions, we develop a
rapidity-dependent thermal model that includes thermal smearing effect and
longitudinal boost. We calibrate the model with thermal yields obtained from a
multistage hydrodynamic simulation. Through Bayesian analysis, we find that our
model extracts freeze-out thermodynamics with better precision than
rapidity-independent models. The potential of such a model to constrain
longitudinal flow from data is also demonstrated.
