The accepted role of RNA within the cell has evolved and expanded alongside the science of microbiology in the last century; from being viewed as a minor player of the biological process in the past its accepted role has grown into the current view of RNA as a central component of all the cellular machinery. Together with the encouraging results of relatively recent explorations into the possibility of using RNA as a method of controlling gene expression, this present view of RNA demands greater understanding and knowledge so as to harness its scientific, and perhaps more pressing, its medical potential. While there already exist a wide range of tools for the prediction of a given strand's secondary as well as functional structure, none have achieved the levels of accuracy necessary to further the exploration of this very attractive approach to therapy. The linearity of the current standing model of RNA folding is what affords this talk's ability to focus only on the prediction of an RNA's secondary structure. More precisely, we ultimately aim at the development and incorporation of heuristics or rules for predicting non-canonical base pairs, of which some estimates say make up an average of up to 40% of natural base pairings, into current dynamic/recursive algorithms designed for secondary structure prediction. The talk will propose first steps towards this incorporation, outline standing challenges, and explore further steps in this direction.