During the last few decades, Peru has experienced numerous natural phenomena (e.g., earthquakes, tsunamis, debris flows, etc.) that have caused considerable economic and human losses. However, the most prevalent phenomenon in Peru is earthquakes due to its geographic location (e.g., Ancash 1970 (7.9 Mw), Pisco 2007 (7.9 Mw), Arequipa 2013 (7.1 Mw), etc.). Therefore, in this research, we focus on improving the techniques for identifying the level of seismic hazard through a set of parameters specific to the territorial conditions. Thus, due to the antecedents presented in the city of Pisco, it has been chosen as a case study. In this sense, a systematic review of parameters and techniques used to determine the level of seismic hazard of a given sector was carried out. Then, the availability of information on the parameters previously identified was evaluated in order to obtain that the most representative variables of the territory are: soil type, slope and soil liquefaction. We consider that this set of parameters is compatible with machine learning techniques or any other method established by the corresponding authorities related to risk and disaster management. Finally, these parameters are applicable and reproducible at any territorial scale.