With the aim of identifying the impact of the Covid-19 pandemic on postgraduate courses (stricto sensu) at the Federal University of Ceará (UFC), the Data Envelopment Analysis (DEA) multi-criteria methodology was adopted, using the BCC modeling oriented to the outputs (BCC-O), proposed by Banker et al. [1]. This methodology was used to carry out a longitudinal analysis of the period leading up to the pandemic (2018 and 2019) and the pandemic period (2020 and 2021). An ex-ante and ex-post-facto study was carried out, taking postgraduate courses as the scenario, specifically the academic and professional master's courses at the UFC. One could see that although the Covid-19 pandemic had an impact on the performance of this university's master's courses, in general, their relative efficiency did not fall so significantly, as it varied from an efficiency score of 0.808 in 2018 and 0.8009 in 2019, to 0.7685 in 2020 and 0.7401 in 2021. In addition, some master's courses succeeded in maintaining their relative efficiency, remaining as efficient units (score 01) over the four years, while others, such as the Master's in Public Policy Evaluation - Professional, and the Master's in Public Policies and Management of Higher Education-Professional (POLEDUC), boosted their indexes. One concludes that the DEA methodology, besides identifying the best practices during the pandemic period, can guide managers in monitoring the courses portrayed as inefficient.