OBJECTIVES: The U.S. Agency for Healthcare Research and Quality (AHRQ) solicited the development of guidance for modeling and simulation studies conducted in the context of health technology assessment. METHODS: We updated and expanded existing systematic reviews of recommendations for the conduct and reporting of modeling and simulation studies in healthcare. We also solicited input from a multidisciplinary team of clinical, policy, and decision analysis experts. The results of the systematic review were then discussed in person with a panel of 28 stakeholders including patient representatives, providers and purchasers of care, payers, policy makers, and principal investigators. Stakeholders commented on existing recommendations and identified gaps, limitations, and areas for elaboration. We subsequently reviewed the websites of 126 health technology assessment organizations that provide guidance on the conduct and reporting of decision and simulation models. We sought additional input from senior researchers with experience in modeling and simulation within AHRQ and its Evidence-based Practice Centers, and from external reviewers. RESULTS: We developed principles and good practice recommendations for modeling and simulation studies conducted to enhance and contextualize the findings of systematic reviews. The guidance applies to structural mathematical models and simulation experiments based on such models. The recommendations address model identification, estimation, and evaluation, as well as the use of sensitivity, stability, and uncertainty analyses throughout model development and use. Recommendations are organized by whether they pertain to the model conceptualization and structure, data, consistency, or the interpretation and reporting of results. We provide the rationale for each recommendation, with supporting evidence or, when adequate evidence was lacking, best judgment. CONCLUSIONS: We present systematically developed guidance for modeling and simulation in the context of health technology assessment. We are hopeful that this work will contribute to increased use of modeling and simulation in conjunction with systematic reviews.