Objectives: Many decision-analytic models with varying structures have been developed to inform resource allocation in chronic obstructive pulmonary disease (COPD). The purpose of this study was to review COPD models for their adherence to the best practice modeling recommendations and their assumptions regarding important aspects of the natural history of COPD. Methods: A systematic search of English language papers reporting on the development or application of a decision-analytic model in COPD was performed in MEDLINE, EMBASE, and citations within reviewed papers. Studies were summarized and evaluated based on their adherence to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS). They also were evaluated for the underlying assumptions about disease progression, heterogeneity, comorbidity, and treatment effects. Results: 49 models of COPD were included. Decision tree and Markov models were the most popular techniques (43 studies). Quality of reporting and adherence to the guidelines were generally high, especially in more recent publications. Disease progression was modeled through clinical staging in the majority of studies. While the majority (n=43) had incorporated some aspects of COPD heterogeneity, only 8 reported the results across subgroups. Only 2 evaluations explicitly considered the impact of co-morbidities. Treatment effect had been mostly modeled as both reduction in exacerbation rate and improvement in lung function (20). Conclusions: Many COPD models have been developed, generally with similar structural elements. COPD is highly heterogeneous and comorbid conditions play an important role in its burden. However, these important aspects have not been adequately addressed in the majority of the published models.