The decision making at the time of manuscript submission typify an important challenge in all scientific fields including immunology. Some discussion about the importance of journals Impact Factors (IFs) has been occurring in the last years and some alternative metrics have been proposed, however, many grants and academic positions still consider IFs as a pivotal criterion. Here we propose an innovative way to analyze journals quality with the aim of generating a simplified and easy-to-interpret approach that can classify journals in three main groups. Our hypotheses were proposed after empirical analyses of the Web of Science InCitesTM Journal Citation Reports (InCites JCR - 2017) considering simultaneously the data related to the IFs and number citable items (CIs) in a 5-year interval. In this process, we could suggest three groups of journals according to its progress in the evaluated parameters, these groups were named as “good” (stable IFs and CIs), “bad” (increasing IFs with stable CIs) and “ugly” (decreasing IFs with or without augmented CIs) journals. We apply this analytic tool in the journals of the Immunology categories and we could observe excellent results. We also compare the grouped journals with the IFs and CIs results published in the following year and observed the full maintenance of those journals in this short-interval. In conclusion, our hypotheses yield an easy-to-interpret tool that can collaborate on journals choice avoiding predatory journals and future unpleasant surprises about journals quality mainly based on IFs.