Decision makers overcome computational limitations by allocating their limited cognitive
resources to the most important information. We seek to investigate whether decision makers also strategically allocate metacognitive resources when making computationally complex decisions. We randomly assigned participants (n = 815) to complete a multi-attribute choice task that included four or eight attributes. Participants then self-reported the weight they placed on each attribute. We compared the alignment between their stated weights and weights estimated from their choices – a measure of metacognitive knowledge. Participants in the 8-Attribute condition had less accurate metacognitive knowledge. This effect was driven by less accurate metacognitive knowledge only for low-importance attributes. Metacognitive knowledge for high-importance attributes was equally accurate across conditions. This suggests that, as tasks become more resource intensive, decision makers strategically allocate their limited metacognitive resources to the most important attributes. In other words, decision makers engage in resourcerational strategies to optimize metacognitive outcomes.