The field of information technology is experiencing rapid advancements, presenting significant challenges in security and privacy for cybersecurity professionals. Research indicates a concerning increase in the development of new malware strains. A perpetual cycle exists between the evolution of malicious software and the efforts to safeguard against them. Antivirus companies continually update their malware signatures, while attackers persistently seek ways to evade detection. Machine learning offers promising capabilities for detecting malware, with feature extraction as the initial step and classification as the subsequent phase. The effectiveness of classification algorithms is influenced by the quality of the extracted features. This articles aim is to assist aspiring researchers in selecting suitable algorithms for their investigations.