Abstract: Diabetic foot ulcer (DFU) is a severe complication of diabetes mellitus, characterized by high incidence, high recurrence and a substantial healthcare burden. Conventional diagnostic and therapeutic approaches have limitations in early identification, precise diagnosis and individualized treatment. In recent years, the rapid development of intelligent technologies, including artificial intelligence (AI), internet of things, advanced materials and digital health care, has provided new solutions for the full-course management of DFU. AI-driven risk prediction models can integrate multidimensional clinical information to improve the accuracy of identifying high-risk populations. Intelligent imaging technologies enable noninvasive, multi-level assessments of tissue structure and function. Wearable devices and telemedicine facilitate continuous monitoring and early warning. Smart dressings and intelligent offloading devices show promising prospects for precise intervention and promotion of wound healing. However, these technologies still face several limitations such as insufficient external validation of models, relatively limited clinical evidence, high device costs, a need to improve long-term stability and patient adaptability, as well as inadequate standardization and equitable accessibility. Taking the disease evolution of DFU as the main logical thread, this review systematically summarizes the application progress of intelligent technologies at different stages and analyzes their strengths and limitations from the perspective of clinical translation. Unlike prior reviews that mainly focus on a single technology or a single stage, this review emphasizes multi-technology integration and a full-process management perspective, aiming to provide references for optimizing intelligent and precision management strategies for DFU and promoting their clinical implementation.