In recent decades, there has been an increase in the frequency and intensity of natural disasters. The world wide growth of population, and consequently of infrastructure, increases the exposure to risks of this type. The expectation that the frequency of such disasters will increase amplifies the need to act today, to minimize the associated economic risks and costs in the future. The ability of buildings to maintain or restore their functionality after disruptive events, within a certain period, has increasingly attracted the attention of academics and professionals. This work intends to study and develop a method to measure the resilience of built assets. Therefore, a resilience classification system is proposed, which assesses resilience according to 5 dimensions (environmental, economic, organizational, social, and technical), which are subdivided into 16 indicators and 75 parameters. This proposal is based on various existent systems such as REDi or Building Scorecard, and its applicability is tested with 11 buildings with varied uses. The results are analysed via SPSS using a Pearson correlation coefficient matrix and clustering techniques. These empirical cases allowed improvements in the system initially proposed. The proposed resilience classification system allows classifying and comparing the performance of buildings, identifying their vulnerabilities, essential information to establish investment priorities. Multiple stakeholders are involved in the life cycle of buildings that may benefit from the developed proposal. The work carried out is in its early stages of development and includes the identification of improvements to be developed in future work.