The RoboCup, an international robotics competition, serves as a platform to improve robot capabilities. In the RoboCup Soccer leagues, continuous enhancements target critical aspects like robot perception, locomotion, shooting, and decision-making. This paper introduces a novel decision-making strategy based on a mental simulations architecture integrating prediction algorithms to anticipate diverse potential outcomes of ongoing actions. Implemented within the context of a goalkeeper scenario in the RoboCup Soccer 3D simulation league, this strategy allows the robot to recognize potential future threats, thus preventing the opposing team from scoring opportunities. A comparative analysis demonstrates the efficacy of employing complex algorithms over traditional decision-making approaches such as state machines. Notably, as the complexity of the robot’s operating environment increases.