BayeFit is a module for Python that allows users to fit, plot, and extract parameter estimates from models of psychophysical data using Bayesian inference. The module makes extensive use of the module PyStan, which in turn makes extensive use of the package Stan, a powerful tool for Bayesian inference using a No-U-Turn sampler. Although PyStan provides an interface between Python and Stan, defining models for use with PyStan can be difficult for most users given the models are defined in C++ language. BayesFit removes this barrier to entry by providing researchers with functions that streamline the process of defining psychophysical models, obtaining fits, extracting outputs, and visualizing fitted models. The source code for BayesFit is available at https://github.com/slugocm/bayesfit. This module can be expanded and reused as newer versions of Python are developed to ensure researchers always have a tool available to ease the process of fitting models to psychophysical data.