Santos, Eliana Elizabet dos creator Sena, Nathalie Cruz creator Balestrin, Diego creator Fernandes Filho, Elpidio Inácio creator Costa, Liovando Marciano da creator Zeferino, Leiliane Bozzi creator text periodical abstract or summary bl. continuing eng Abstract Fire behavior prediction models can assist environmental agencies with fire prevention and control. This study aimed to adjust a fire prediction model for the state of Minas Gerais, Brazil. Using the R program and hotspots provided by the National Institute for Space Research (INPE) for 2010, prediction of the probability of fires through the Random Forest algorithm was conducted using the Bootstrapping method. The model generated a prediction map with global kappa value of 0.65. External validation was performed with hotspots in 2015. Results showed that 58% of the hotspots are in areas with ignition probability > 50%, being 24% of them in areas with 25-50% probability, and 17% in areas with < 25% probability. These results were considered satisfactory, demonstrating that the model is suitable for predicting fires. Keywords: fires; modeling; environmental monitoring. Publicação on-line; 19 ref.; 1 table; 5 illus.; Summary (En) INCÊNDIO FLORESTAL PROFILAXIA MEIO AMBIENTE PROTEÇÃO FLORESTAL Rio de Janeiro-RJ Instituto de Florestas - UFRRJ 1994 2025-0457 1415-0980 / ISSN 2179-8087 0nline BR2026001341 v. 27(3) p. 1-7; (2020) https://www.scielo.br/j/floram/a/8wNh9YJtKttDHqTMWzwJFpg/?format=pdf&lang=en https://www.scielo.br/j/floram/a/8wNh9YJtKttDHqTMWzwJFpg/?format=pdf&lang=en BR-BrBNA 260601 20260601103716.0 eng