Manual alignment of Insect ribosomal RNA-encoding sequences (rDNA) using base-pair covariation as a criterion to delimit stem and loop regions is time-consuming, and sometimes considered to be subjective. It is, however, necessary in many cases, as automated alignments cannot yet avoid the misalignment of rDNA sequences in highly length-variable regions (i.e., expansion segments). Manual alignments guided by structure provide a great number of hypotheses that can be tested through the addition of new sequences. For taxa closely related to those already included in an existing alignment, the manual alignment process is relatively trivial, making this process an excellent candidate for automation. Data from consensus sequences and the relative position of conserved motifs across an alignment should be of use in predicting homologous regions in unaligned sequences. As more sequence data are incorporated into multiple alignments, prediction of possible homologous regions in unaligned sequences should become more accurate. A first step towards automating the predictive process is simple characterizations of existing alignments, for which we provide several scripted methods. Additionally, we explore possible means of predicting homologous regions via these characterizations using examples from our existing manual alignments which span the Insecta.