The implementation of methods which belong to the field of Artificial Intelligence such as the Artificial Neural Networks (ANN) based methods is continuously increased in many scientific and technological applications. As regards the civil engineering applications, the investigation for the utilization of these methods has led to very promising results. More specifically, the experimental application of ANN-based methods for the seismic vulnerability assessment of structures has proved that they can be utilized as alternative methods in parallel of the well-documented existing methods. However, despite their promising results there is no wide acceptance of ANNs as computational tools for the prediction of the seismic damage level of structures. This can possibly be attributed mainly to the fact that the vast majority of civil engineers who investigate methods for structures’ seismic vulnerability assessment has no the minimum required background about the abilities and the utilization of the ANN-based methods. The current paper attempts to present a different point of view of the ANN-based methods and to prove that the research for their further implementation can be approachable by civil engineers provided that the corresponding formulation is defined in certain stages. In the framework of the current paper it is also proved that by the utilization of ANNs the definition of relatively simple equations for the preliminary estimation of the seismic damage level of R/C buildings in near-real time is possible.