Effective and efficient Scenario-Based Training (SBT) is sequenced using well-grounded instructional strategies and learning theory. The primary instructional strategy employed by the Military requires that SBT is sequenced in a “crawl-walk-runâ€� trajectory. For software to sequence scenarios effectively and efficiently in this manner, SBT needs objective, computational values of a scenario's complexity, but designers, software engineers and trainers operate without the necessary tools to objectively calculate Scenario Complexity (SC). This results in subjectively sequenced SBT that may be ineffective, inefficient, or designed without attention to sound instructional practices. To address this issue, research in education, task complexity, task framework and cognitive resource principles was integrated and an innovative SC tool (patent pending) comprised of an algorithm and supporting process, was developed to objectively and computationally define SC. This paper presents findings from the use of the SC tool to validate a training matrix embedded in the United States Marine Corps' M1A1 Advanced Gunnery Training System. To establish that the SC tool is accurate and effective, it was first necessary to determine how consistent the Subject Matter Expert (SME) evaluations of the scenario's characteristics were. Then, using the results of their input to the SC algorithm, determine how well the SME sequencing matched that of the training matrix. The objective was to use the SC tool to verify and validate the “crawl-walk-runâ€� sequencing of the training matrix and identify any areas in need of adjustment. After employing the SC tool, quantitative analyses showed that the SMEs were very consistent in their formulations. Importantly, the SC tool revealed that the training matrix deviates alarmingly from “crawl-walk-runâ€� sequencing. This paper also presents the study's methodology and algorithm, lessons learned and the future impact that this innovative SC tool may have upon design, development and evaluation of SBT and automated, adaptive training.