Against the global rollout of Carbon Border Adjustment Mechanisms (CBAMs), carbon tariffs have emerged as a core tool for developed economies to internalize environmental externalities—especially for energy-intensive imports that dominate cross-border carbon flows. However, emission information asymmetry, a critical barrier to implementing cross-border energy and environmental policies, undermines the design of optimal carbon tariffs, as it distorts the link between tariff levels and actual fossil energy-related emissions. This study develops a two-country analytical model to examine how biased assessments of exporters’ carbon intensity influence optimal tariff settings, exporters’ strategic behavior, and aggregate carbon emissions—with a focus on energy-intensive production contexts. The results show that underestimating carbon intensity reduces exporters’ compliance costs, incentivizing emission concealment; this weakens tariffs’ environmental stringency and may raise global emissions. Overestimation, by contrast, inflates exporters’ marginal costs, discouraging green investment and causing emission displacement rather than reduction. The analysis highlights a policy feedback loop wherein misjudged emission information distorts both trade competitiveness and environmental performance. This study concludes that a transparent, accurate, and internationally verifiable carbon accounting system is essential: it not only facilitates the effective implementation of CBAM but also aligns optimal carbon tariffs with CBAM’s dual goals of climate action and trade equity, while supporting global energy transition efforts.