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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.