This provides an ipython notebook that implements maximum likelihood estimation (MLE) powerlaw fits for fast radio burst (FRB) fluence distributions, compares these to least-squared fits, and finds the MLE methods are significantly more robust, as detailed in Bilous et al. 2024 (arXiv:2407.05366).