Mobile forensics has emerged as one of the most important areas within the field of digital forensics, given that mobile devices are ubiquitous and offer gigabytes of data. Mobile forensics is a process for recovering data from mobile devices, such as smartphones and tablets, and then analyzing it for purposes of aiding criminal investigations, legal proceedings, or cybersecurity efforts. As the complexity of mobile phones increases, so does the data; it is surprising to find that traditional forensic techniques often fall short in efficiently and effectively analyzing that amount of information. Machine learning (ML) has recently been proven to be one of the subsets of AI that is a very important tool in solving the problems and issues of mobile forensics. Its algorithms enable systems that can learn from data, which improves their performance over time in identifying patterns, anomalous patterns, and classifying data in ways humans are not capable of performing. The integration of ML helps improve the detection of digital artifacts, automate most tedious actions, and provide predictive insights that can be used proactively during investigations.