modleR is a workflow designed to automatize and document some of the common steps when performing ecological niche models (ENM). Given the occurrence records and a set of environmental predictors, setup_sdmdata() prepares the data by cleaning for duplicates, removing occurrences with no environmental information and applying some geographic and environmental filters. It also partitions data into test and training sets, using crossvalidation or bootstrap procedures. do_any()or do_many() fit the ecological niche models using several algorithms, some of which are already implemented in the dismo package (Hijmans et al 2017), and others come from other packages in the R environment, such as glm, Support Vector Machines (kernlab and e1071) and Random Forests (randomForest). A function to join individual partitions in several ways is provided in final_model(). Finally, ensemble_model() assembles models from distinct algorithms and provides summary rasters.