Using the new Rational Numbers Excel Add-In described in this book, the mathematical and graphical powers of Excel can now be applied to analyzing mass spectral data obtained using LCMS (liquid chromatography-mass spectrometry). This Excel Add-In is designed to help identify small molecules from less-than-perfect mass spectral data. All data must be accurate mass fragmentation data with a minimum accuracy of +/- 5 mDa, which has become common recently. This book is not concerned with the technical or experimental aspects of ion formation, mass selection or mass measurement; it deals primarily with the analysis of accurate mass fragmentation data of small singly-charged analytes. In this book, there are no fragmentation rules, chemical drawings of hypothetical fragment ions, or quantum mechanics. This book is also not an attempt to review the literature of computational approaches to mass spectral interpretation. This book is basically the author's perspective about a different approach that can help chemists, not just mass spectrometrists, to identify analytes quickly from LCMS data generated using electrospray ionization. When a limited set of data is basically converted into graphical representations with a few scores, it is important to understand the underlying operations and heuristic assumptions that are being made. First, there is a brief description of partitioning (Chapter 1). Three properties of atoms and combinations of atoms (mass, isotopic frequency, and valence) that are critical to mass spectrometry are described in Chapter 2. These three properties, base rates, and other considerations can then be used to find plausible subfragment masses while excluding many spurious masses (Chapters 3 and 4). In Chapter 5, combinations of plausible subfragment masses are systematically generated and checked to find mathematical partitions of the molecular weight. The best partitions are partitions of the molecular weight which also have combinations of subfragments that can explain many of the more intense fragment ions. These sets of partitions are sets of subfragment masses which are not aligned in space at this point. In Chapter 6, permutations of these combinations of subfragment masses are systematically generated and checked against truth tables to find spatial alignments of the subfragments in modular structures that are consistent with the mass spectral data. Up to this point, all operations in the Excel Add-In were done using masses (numbers); in Chapter 7, the subfragment masses are converted into formulas. Some minor adjustments to scoring are described in Chapter 8. Basic data considerations are described in Chapter 9. In Chapter 10, examples of using the Excel Add-In are described in some detail.