Three-dimensional concrete printing (3DCP) is regarded as a key enabling technology for intelligent construc-tion because high construction efficiency, reduced material waste, and geometric freedom can be achieved. However, stable print quality is challenged by the coupled effects of material rheology, machine motion, and environmental variations. In this paper, quality-control research for 3DCP is systematically reviewed from a multidisciplinary perspective. The principal quality-related factors and their mechanisms are first analyzed. Experimental, physics-based, and data-driven modeling approaches are then compared in terms of applicabil-ity, accuracy, generalizability, and computational cost. Subsequently, representative quality-control strategies involving mechanical systems, process-parameter optimization, sensing, and closed-loop regulation are evalu-ated. On this basis, the major research difficulties are identified as nonlinear time-varying material-process-environment coupling, discontinuities across flow-deposition-hardening scales, limited cross-material and cross-equipment data generalization, and sensing-computation-actuation delays. Future priorities are proposed for dynamic safe-window identification, physics-informed hybrid modeling, verifiable closed-loop control, and standardized project-level qualification. It is concluded that scalable application of 3DCP requires quality assurance to be shifted from offline parameter setting and post-process inspection to an integrated workflow of experimental calibration, online sensing, constrained control, and performance verification. The review is expected to provide theoretical and technical support for reliable implementation of 3DCP in intelligent con-struction.