Cell migration is crucial for many biological processes, including normal development, immune response, and tissue homeostasis and many pathological processes such as cancer metastasis and wound healing. Microfluidics has revolutionized the research in cell migration since its inception as it reduces the cost of studies and allows precise manipulation of different parameters that affect cell migratory response. Over the past decade, the field has made great strides in many directions, such as techniques for better control of the cellular microenvironment, application-oriented physiological-like models, and machine-assisted cell image analysis methods. Here we review recent developments in the field of microfluidic cell migration through the following aspects: 1) the co-culture models for studying host-pathogen interactions at single-cell resolution; 2) the spatiotemporal manipulation of the chemical gradients guiding cell migration; 3) the organ-on-chip models to study cell transmigration; and 4) the deep learning image processing strategies for cell migration data analysis. We further discuss the challenges, possible improvement and future perspectives of using microfluidic techniques to study cell migration.