Sloppy model publications offer a useful approach for finding the stiff and sloppy parameter combinations based on Fisher Information. Fisher information is well known and used in several fields but, to the knowledge of the author, is not currently used in magnetic resonance relaxation analysis. Useful properties of Fisher Information have been concisely summarized and didactic introductions are found via the sloppy model citations given above, and elsewhere . Since Fisher Information can be used as a unique metric defining distances between probability distributions, it is a foundational concept in the field of Information Geometry . Here, only a simplified view of Fisher Information can be provided, and a few of the key results used in this report are listed.