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In recent years, Levy flight (LF) is increasingly being employed as search mechanism in metaheuristics optimization algorithms (MOA) to solve complex real world problems. LF-based algorithms are found to exhibit superior or equivalent results to their non-LF counterparts and are expected to be advantageous in situations where no prior information is accessible, the targets are challenging to ascertain, and the distribution of targets is scarce. It has emerged as an alternative to Gaussian distribution (GD) to achieve randomization in MOA and have applications in diverse biological, chemical, and physical phenomena. The purpose of this article is to make the readers acquainted with the applicability of LF in some of the latest optimization algorithm applied in the field of metaheuristics. Also the present study deals with examination of basic underlying principle in the working of LF along with their related properties.