Background: The combination of amivantamab and lazertinib (AL) has demonstrated clinically significant efficacy in patients with previously untreated EGFR-mutated advanced non-small cell lung cancer (NSCLC). However, its economic value relative to the standard therapy, osimertinib, remains unclear. This study evaluates the costeffectiveness of AL regimen compared with osimertinib in US and Chinese healthcare settings. Methods: A partitioned survival model, comprising progression-free survival (PFS), post-progression, and death states, was developed using a Markov model. Clinical data were obtained from the recent Phase III MARIPOSA trial. Direct medical costs (including drug acquisition, administration, and adverse event management) were obtained from US and Chinese healthcare system data, public databases, and the literature. Health-state utilities were sourced from the literature. Incremental cost-effectiveness ratios (ICERs) were calculated based on quality-adjusted life years (QALYs). Threshold analysis was performed to identify pricing strategies at specified willingness-to-pay (WTP) thresholds. Model robustness was assessed through sensitivity and scenario analyses, and additional subgroup analyses performed. Results: In the base case analysis, the average costs of AL and osimertinib regimen were $1,030,524.3 (China: $234,270.87) and $466,922.0 (China: $20,075.35), respectively, and the QALYs achieved were 4.08 (China: 3.66) and 2.60 (China: 2.66), respectively. The ICERs for AL compared with osimertinib in the US and China were $563,602.3 and $214,195.51, respectively. Based on the respective WTP thresholds in the US and China, the AL regimen did not represent a cost-effective option. Sensitivity, scenario, and subgroup analyses confirmed the robustness of these findings. Conclusions: Although AL regimen prolongs QALYs compared with osimertinib, it may not meet cost-effectiveness thresholds given current US pricing and simulated Chinese prices. These findings emphasize the need to consider policy implications and future pricing strategies.