Mobile cloud forensic process models aim to establish systematic, reliable, and legally valid procedures for investigating crimes involving data distributed between mobile devices and cloud environments. Research in this field focuses on designing end-to-end frameworks that address evidence identification, acquisition, preservation, examination, analysis, and presentation within hybrid infrastructures. Key areas include developing unified process models that integrate both mobile and cloud evidence handling, automation of evidence collection across multiple service providers, and synchronization of volatile and non-volatile data sources. Emerging research topics also encompass blockchain-based forensic chain of custody, standardization of mobile cloud forensic methodologies, and privacy-preserving forensic workflows. Furthermore, the incorporation of artificial intelligence for dynamic evidence correlation, forensic readiness models for proactive investigation, and cross-jurisdictional legal compliance in mobile cloud investigations are gaining increasing attention in advancing the robustness and reliability of forensic process models.