Warfighters are expected to detect threats by quickly observing and identifying relevant pattern changes in the environment. However, little formal and adequate experiential training exists for behavior cue detection. A technique proposed to improve these pattern recognition skills, through developing an individual's capacity to observe and remember details, is Kim's game. During Kim's game, trainees must examine multiple objects for a period of time and later recall details of what was shown, by memory. Considering the U.S. Army's focus on utilizing Simulation-Based Training to bridge the gap between traditional classroom-based and live training, this research investigated a virtual simulation of Kim's game for pattern recognition training. The Kim's game task involved identifying kinesic target cues (i.e., aggressiveness and nervousness) amongst non-target cues in a virtual environment. The objective for this experiment was to compare the effectiveness of two virtual simulations, the Kim's game group and a control group, by evaluating different performance metrics of detection accuracy, response time, and false positive detection. In addition, the relationship between an Operation Span Task and performance was analyzed. A series of one-way between-groups analysis of variance revealed no significant difference in post-test performance. An examination of the percent change for the means provided insight into the post-test performance between Kim's game and the control group. The results showed that the control group performed better than the Kim's game group in detection accuracy, and differed at a statistically significant level for improved response time. The results of the percent change for the means also suggested that Kim's game had a marginally greater decrease in false positive detection. Recommendations include the use of Kim's game for enhancing memory in safety-critical domains. Ultimately, this paper seeks to explain the performance outcomes and offer insight into the advancement of human behavior cue detection research.