<p>Unmanned Aerial Vehicle (UAV)–vehicle cooperative delivery has emerged as a promising paradigm for addressing the growing complexity of urban and regional logistics. By combining the capacity and network coverage of ground vehicles with the flexibility and accessibility of UAVs, such systems offer new opportunities to improve delivery efficiency, responsiveness, and sustainability across diverse operational contexts. In recent years, research in this field has expanded rapidly, producing a wide range of models, algorithms, and application-driven studies. This paper provides a comprehensive review of UAV–vehicle cooperative delivery research, synthesizing advances in system configurations, coordination mechanisms, modeling approaches, and solution methodologies, including optimization-based, heuristic, hybrid, and learning-driven frameworks. Empirical evidence from major application domains, such as urban parcel logistics, emergency and humanitarian operations, infrastructure inspection, and on-demand services, is examined to reveal how system design and operational conditions jointly shape performance. Beyond summarizing existing work, this review identifies fundamental modeling, operational, and sustainability challenges that continue to hinder large-scale deployment, including synchronization fragility, energy and uncertainty management, regulatory constraints, and scalability. By consolidating fragmented research strands into a unified analytical perspective, this review aims to support the transition of UAV–vehicle cooperative delivery from isolated pilot studies toward robust, scalable, and policy-relevant transportation systems.</p>