This work explores the following applications of graph theory to plasma chemical reaction engineering: assembly of a weighted directional graph with the key addition of reaction nodes, from a published set of reaction data for air; graph visualisation for probing the reaction network for potentially useful or problematic reaction pathways; running Dijkstra's algorithm between all species nodes; further analysis of the graph for useful engineering information such as which conditions, reactions, or species could be enhanced or supressed to favour particular outcomes, e.g. targeted chemical formation. The use of reaction-nodes combined with derived parameters allowed large amounts of key information regarding the plasma chemical reaction network to be assessed simultaneously using a leading open source graph visualisation software (Gephi). A connectivity matrix of Dijkstra's algorithm between each two species gave a measure of the relative potential of species to be created and destroyed under specific conditions. Further investigation into using the graph for key reaction engineering information led to the development of a graph analysis algorithm to quantify demand for conditions for targeted chemical formation: Optimal Condition Approaching via Reaction-In-Network Analysis (OCARINA). Predictions given by running OCARINA display significant similarities to a well-known electric field strength regime for optimal ozone production in air. Time dependent 0D simulations also showed preferential formation for O center dot and O-3 using the respective conditions generated by the algorithm. These applications of graph theory to plasma chemical reaction engineering show potential in identifying promising simulations and experiments to devote resources.