Gaps in human performance resulting from a lack of skills and knowledge require solutions – interventions. The process of selecting the most effective intervention (solution) for closing a skills and knowledge gap - such as classroom training, e-Learning, Structured on-the-job Training (SOJT), or job-aid - is a fundamental and vital practice for Human Performance Technology (HPT) practitioners. Unlike other activities in the Performance Improvement/HPT (PI/HPT) model, the activity of intervention selection is ambiguous. Meaning, there is currently no systematic process or tool in place for selecting learning and performance-improvement solutions that is reflective of the learning science. Consequently, the critical activity of intervention selection is often more art than science, especially in contrast to other phases of the PI/HPT model. HPT is, first and foremost, a technology. HPT practitioners apply scientific and organized knowledge to practical ends using rigorous inquiry to provide initial evidence of possible interventions for performance gaps (Stolovitch, 2015). The results-driven approach of HPT empowers performance-improvement practitioners to select and design interventions that are beyond the scope of traditional classroom training. The ambiguity of the intervention selection process presents a persistent challenge for HPT practitioners when selecting between learning and performance?support solutions as well as determining specific modalities for delivery. The United States Coast Guard have been exemplar practitioners of HPT for over two decades, but the need for a systematic intervention selection methodology persisted. To address the need for a new process, a systematic decision-aid tool was developed called the Learning Intervention Type and Modality (LITAM) tool. The tool was designed to integrate seminal literature and research in the learning science field relative to train-to-memory decisions, and modalities of instruction. The LITAM tool was put through rigorous field-testing and evaluations, which validated that these new methods for generating performance intervention recommendations were both accurate and effectual.