n identification of severe acute respiratory syndrome corona virus 2(SARS-CoV-2), the novel corona virus responsible for COVID-19, professionals related to medical domain have been entered to implement various novel technical solutions and patient diagnosis techniques. The COVID-19 pandemic has accelerated enforcement of machine learning (ML) technology, and various other such organizational groups have been eager to embrace and adjust these ML techniques to the outbreak concerns. We have carried out a tremendous analysis based on the literature available till now. The complete assessment carried related to the use of machine learning models to fight against COVID-19, emphasis on various aspects like disease effects, it’s diagnosis, percentage of severity estimation, drug and treatment analysis, effective feature selection, and also post-Covid context related. A systematic search of online research repositories which are Google Scholar, Web of Science and PubMed was undertaken in corresponding to the "Preferred Reporting items for Meta-Analysis and Systematic Reviews" criteria to find all related published papers during 2020 and 2022 years. The search process was created by integrating COVID-19-typical terms with the word "machine learning."

World Health Organization, Coronavirus Disease 2019, Disease Diagnosis, Machine learning, Support Vector Machine, Deep Forest, Extreme Gradient Boosting, Chest X-rays.