During recent years, supply chain risks have gained importance in the food supply chain. This study presents a methodology to analyse the risk in the agri-food supply chain belonging to the Andean region in Peru. It utilises the interpretive structural modelling (ISM) with matrice d' impacts croises multiplication appliqué an classement (cross-impact matrix multiplication applied to classification, abbreviated as MICMAC) to identify and understand relationships between risk types. Based on the empirical data collected from the food industry experts, ten risk factors were identified as relevant. Finally, the identified risks were classified using ISM-MICMAC methodology. The research findings demonstrated that natural disaster, environmental, and legal risks were the most substantial. The findings highlight that selected methods are capable of recognising the most substantial risks that are most critical to assess, manage with adequate mitigation actions from the practitioners in the agri-food industry.