Technical Abstract: The massive quantity of data produced by next-generation sequencing has created a pressing need for advanced statistical tools, in particular for analysis of bacterial and phage communities. Here we address estimating the total diversity in a population – the species richness. This is an important statistical problem with a rich literature, but to date only relatively simple methods have been implemented in readily available software. There is a need for a software package employing modern, computationally-intensive statistical procedures, with error terms, goodness-of-fit assessments, and robustness comparisons. The same methods also apply to estimating the total size of a population. We present CatchAll, a fast, easy-to-use, platform-independent software package which uses optimized numerical searching to compute maximum likelihood estimates for finite-mixture models, linear regression-based models with non-diagonal weight matrices, and all existing coverage-based nonparametric methods, while accounting for outlier detection/deletion and other data-analytic considerations. Given sample “frequency count” data, CatchAll computes 12 different diversity estimates and compares the results via a model-selection algorithm, providing the user with a best overall choice. In addition CatchAll derives model-based discounted estimates of total diversity to adjust for possibly uncertain low-frequency counts. It is accompanied by an Excel-based graphical display spreadsheet program.