Polymeric materials are intricate systems with unique properties across different length and time scales, presenting challenges in understanding the hierarchical features that govern their behavior. Advancing innovative polymeric systems requires a deep comprehension of these complexities. Dissipative particle dynamics (DPD), a mesoscale simulation technique, has proven instrumental in elucidating polymer behavior. Unlike molecular dynamics, which tracks individual molecules, DPD employs a coarse‐graining approach, to describe molecular systems as particles interacting via soft potentials. Thanks to its computational efficiency, DPD has enabled researchers to numerically study several complex fluid applications in detail. Moreover, with the ever‐increasing high‐performance computing resources, it has become possible to tackle larger molecular systems beyond the nanoscale, typically micrometer‐sized systems. An in‐depth analysis of the theoretical foundations of DPD is presented, focusing on its methodology, mathematical formulations, and computational implementation. This review then explores various applications of DPD simulations for polymeric systems, demonstrating DPD's ability to accurately capture phenomena such as polymer self‐assembly, polymer behavior in solutions and blends, charged polymers, polymer interfaces, polymer rheology, polymeric membranes, polymerization reactions, and polymeric composites. Overall, this review examines the adoption of DPD as a predictive modeling tool for polymeric materials, focusing on its key features and its integration with methods such as atomistic molecular dynamics to determine the interaction parameters. Building on these advancements, future directions for DPD include its potential applications in other systems like biological membranes, macromolecules, and shape‐memory materials.