The genomes of different organelles make molecular baraminology easier and much more high-throughput, due to the abundance of organelles in the cell and the small size of their DNA. The different classes of plastid and mitochondrial DNA delineate several apobaramins. Differences in gene order, organelle genome size, GC%, codon usage, and gene repertoire can help delineate holobaramins in some cases. In this paper existing organelle genome baraminology studies will be reviewed, as well as resources and algorithms for organelle genome-based molecular baraminology studies. Two new software will be presented in this paper, the Organelle DNA Analysis script, and an app called the Molecular Baraminology Analysis Tool suite. Both tools perform sequence download, alignment, and cluster analysis. The first software is a command line script written in Python, which downloads a list of sequences via Entrez, then performs alignment of these sequences, calculates a sequence similarity matrix, and then performs k-means clustering on the matrix. The software outputs a heatmap, the sequence similarity matrix, baraminic trees of each cluster, and also several plots. This script can be automated on the command line in Linux. The second software is a shiny app written in R, and I accessible online. It allows the user to download a set of sequences from the NCBI database, and then align these sequences to produce a sequence similarity matrix, either using third-party tools or using the app itself. The user can then run a clustering method to calculate putative clusters (baramins), as well as statistics on these clusters. Molecular baraminology-based software can be used to complement morphology-based tools. Since organelle genomes are easily accessible and small in size, these software also allow users to quickly perform baraminology studies.