The study of multiphase flow phenomena has been a major research focus in recent decades due to their importance in various natural and technical processes and their inherent complexity. Microfluidic multiphase flows are critical in numerous engineering applications, such as Lab-On-a-Chip devices, inkjet printing, fuel cells, microreactors, oil-gas/water transport, and CO₂ sequestration in porous media. In these often geometrically complex systems, interfacial forces —particularly surface tension— dominate fluid behavior. Additionally, liquid-gas systems form a contact line with solid surfaces. As the three-phase system strives to reach its equilibrium configuration, it exhibits dynamic behavior determined by its physicochemical properties. Broadly speaking, theoretical models fall into three main categories: those focused on the microscopic scale, particularly molecular dynamics, mesoscopic descriptions like phase field models, and those developed at the continuum level. Combining the outcomes of these three categories can improve modeling and physical understanding. Recently, microscopic (molecular dynamics) simulations have provided a practical way to deepen our understanding of fundamental physics. On the other hand, strong effort has been put into adapting continuum-based modeling high-fidelity Computational Fluid Dynamics methods to the application at hand. Some recent works strive to enrich the existing modeling approaches with the use of data-driven methods. Development of the Machine Learning approaches has opened new research avenues for tackling challenges such as curvature approximation, model discovery for contact line dynamics, and optimization of complex microfluidic systems. Data-driven methods can also improve the efficiency of the numerical modeling of multiscale phenomena. The mini-symposium will bring together researchers working on the different types of micro/meso and macroscopic modeling and simulation of multiphase flows in microfluidic applications as well as the emerging application of data-driven methodologies in multiphase microfluidics. We will discuss the latest research on how data-driven methodologies can improve both microfluidic system designs and the understanding of complex multiphase flow dynamics.