Wire electrical discharge machining (WEDM) is a heat-based, non-contacting and precision machining process which can produce complex geometry in any conductive material regardless of its hardness. Although many studies on the investigations of individual input factors in the WEDM process have been done, no complete study on the frequency weighted correlation of all the key input factors with all the output parameters has been made yet. This paper tries to fill this gap through reviewing peer reviewed journal articles available on Scopus, Web of Science, Science Direct, Springer Link, Taylor & Francis Online, and IEEE Xplore according to PRISMA 2020 methodology. The number of key input and output factors is thirteen and eight respectively and they have been addressed in this paper. Frequency weighted analysis proves that Ton has been mentioned in 63%, Toff in 62%, V in 41%, Ip in 38%, Ra in 62%, and MRR in 48% of all papers. On the other hand, fatigue resistance, residual stresses, geometry deformation, and cutting speed still lack sufficient consideration even though they play a vital role in industry. The literature review also highlights powder mixed dielectrics, coated wire electrode, multi-objective optimization approach, artificial intelligence (AI), non-dominated sorting genetic algorithm (II), technique for order preference by similarity to ideal solution (TOPSIS), and machine learning as areas of emerging interest in improving the machining process. In general, the literature review serves as a good source for understanding the important process variables, current research trends, and gaps, and can be used for multi-objective process optimization and future research.