This paper presents an analysis of the principal systems and tools constituting the state of the art of automated machine learning domain. WilsonIA tool is introduced as a new alternative resource for model creation by non-expert users producing a model that can be further used in the user’s domain of expertise. The results of the study demonstrate the tool’s effectiveness and potential. WilsonIA follows a rule-based AutoML approach, allowing users to exert greater control over the model creation process. This feature is highly relevant and could be adopted by other tools in the future. AutoML tools or systems aimed at non-expert personnel in the area of Machine Learning do not have a level such that they can be installed and operated by this type of users. The objectives are: to create an autoML tool that can be used by experts in their own domain without the need for knowledge in Machine Learning and validate the tool through a case study. The results of this work demonstrate the validity of all the models that were obtained for each of the datasets in the case study, which validates the effectiveness of the tool and its ease of use. WilsonIA is a good alternative to take into account, simplifying the process of obtaining machine learning models, which is useful for both expert and non-expert users.