The tourism industry is very vulnerable, and issues such as natural disasters, infectious diseases, epidemics, economic crises, war, etc., for example, the risks menace the tourism industry. Recognizing these risks and preoperational arrangements are such main concerns. The purpose of this study is to design a risk management model in the Iranian hotel industry,the exploratory mixed research method was used in the study. The statistical population in the qualitative section consisted of academic and tourism industry experts (tourism and risk managers, deputies, and professional tourism organizations and hoteliers), and in the quantitative section, staff of four or five-star hotels in Tehran. Yazd, Isfahan, and Shiraz province in the summer of 1400. In the qualitative area of the study, judgment and snowball sampling methods were used until the theoretical saturation was achieved within twelve in-depth interviews. The interview's findings were then categorized using open, axial, and selective coding. Afterward, in the quantitative section, using a stratified random sampling method, 384 people were selected as a sample, and a questionnaire was distributed among them. Based on the findings of the qualitative part of the research, the tourism risk management model in the Iranian hotel industry in two dimensions (external and internal), consisting of 13 components and ٦, 2indicators, was designed and compiled, and the model was approved. Introduction: Tourism is very sensitive and vulnerable to the glass industry and is exposed to various risks. One of the main reasons for the high vulnerability of this industry is the integration of tourism and travel products, which is the interaction and cooperation of various sectors such as transportation, accommodation, hospitality, etc. (Ziaee et al., 1400). Risk is a multifaceted concept generally associated with the expected adverse effects. (Brast Bauer, 2016). All organizations and systems at any level of performance and at any time and place face various risks that affect their performance and achieve their goals (Asgari, 2010). So the risks can not be eliminated, but they can be better managed to reduce the damage caused. Such an approach is called risk assessment and management, which can help reduce the elements and factors of risk or vulnerability to human societies and their property (Ritchie, 2009). Materials and Method The combined research method and research design are also of the type of mixed exploratory research design (qualitative-quantitative) The main research tools in the qualitative and quantitative stages of the research were as follows: Qualitative stage: Review and study of research and background on the subject. Qualitative stage: In-depth semi-structured interviews with experts. Quantitative step: Using the Likert scale closed questionnaire. The study's statistical population was a qualitative interview with a group of experts. For this purpose, the "snowball" sampling method was used to achieve theoretical saturation. In this section, 12 people were selected. The statistical population of the research in a small part includes the staff of four and five-star hotels in Tehran, Yazd, Isfahan, and Shiraz in the summer of 1400. The sampling method of the study was 384 people. In the qualitative section, in-depth interviews with experts and content analysis techniques in the MaxQDA software environment were used to identify the components and research model components by studying and researching the research and literature on the subject. In the quantitative section, a questionnaire was used to test and quantify the identified model to survey statistical samples and use structural equations (SEM) in LISREL and Smart PLS software. Discussion and Results In the qualitative part of the research, the main focus of the research questions was exploring the factors affecting the dimensions, components, and indicators related to risk management in the hotel industry as the central concept. In the first stage, the main categories and sub-components were presented based on open and centralized data coding from research backgrounds, in-depth and exploratory interviews with key experts, and refinement of conceptual codes. The factor analysis results showed that out of 62 available indicators (items), 13 main components could be identified. In the quantitative part, a questionnaire with 62 items was compiled. Distribution and data were analyzed by exploratory and confirmatory factor analysis with LISREL and Smart PLS software. The risk management model consisted of 62 items, of which 31 were obtained for external risk management and 31 for internal risk management. Standardized parameter estimates showed that all indicators are statistically significant and have high factor loads. The final model of the research was tested and confirmed by structural equation modeling. Conclusions This research seeks to model risk management in the Iranian hotel industry. The spatial scope of this research is four-and five-star hotels in the three cities of Yazd, Isfahan, and Shiraz, and Tehran is concentrated as the gateway for foreign tourists to the country. The importance of effective risk management in all industries has been considered for a long time. In addition to actors and implementers of various industries, national and international regulators have made effective risk management an integral part of their monitoring and control process. This particular importance has attracted a lot of attention in tourism, which is very sensitive and fragile due to its nature. According to the research results, political risk (standard coefficient 0. 702 and values T196. 19), natural environment risk (0. 725 and 0. 1515), legal risk (0. 693 and 20. 452), economic risk (0. 719) 0 and 111/19), social risk (0. 669 and 016. 18), cultural risk (0. 673 and 15. 664), human resources risk (0. 804 and 09. 05. 31), scheduling risk (836/8). 0 and 095/41), execution risk (0. 787 and 31. 761), procurement risk (0. 722 and 08. 05. 32), cost management risk (0. 775 and 30. 729), design risk (0. 764) And 25. 446), and communication risk (0. 819 and 36. 080) were the explanators of the final research model.