The globalisation process and the recent economic crises have increased the development of models to identify the factors related to business bankruptcy. The tourism industry is not immune to this concern, and in the previous literature, bankruptcy prediction models are generally focused on hotels or restaurants. However, there are no experiences of global models for tourism companies. This study develops a global bankruptcy prediction model capable of predicting any activities carried out in the tourism industry with high precision. To this end, a sample of 406 Spanish companies that have developed their activity in three tourism industry sectors (hotels, restaurants, and travel agencies) in the period 2017-2019 has been used. This sample includes bankrupt and non-bankrupt corporations and has allowed the comparison between a global model and various focused models applying artificial neural network techniques. The results have confirmed the superiority of the global model and provide different sample selection and cost minimisation solutions for bankruptcy prediction modelling in the tourism industry