This repository contains the code for QPE-FIT (frozen to version v0.1.11), a Bayesian parameter estimation tool to fit Quasi-Periodic Eruption (QPE) timings. Under the model assumption that QPEs are generated by an extreme mass-ratio inspiral (EMRI) orbiter colliding with the accretion disk around a massive black hole, QPE timings encode information about the EMRI-disk system, and in principle, can be used to learn their underlying parameters. The current version performs paremeter inference via nested sampling using UltraNest; previous iterations (including the one described in the original paper) used Markov Chain Monte Carlo. The included files are all Python source code files (.py format), a README markdown file to describe the functionality and basic documentation (.md format), two example parameter files to run a code example (.json format), and a configuration file for pip-installability (.toml format). As documented in README.md, the code is designed to be installed via pip and should run out-of-the-box. To reproduce the results in arXiv:2602.16776, use the QPE timings and errors presented in Table 1 and the default sampler setup. Please feel free to write to joheen@mit.edu with any questions/comments!