Abstract: Ladle furnace (LF) refining can effectively control the composition and temperature of molten steel and plays a role in cushioning and coordinating the production rhythm between steelmaking and continuous casting. The use of models for control and decision-making in LF refining can further standardize the refining operations, improve the quality and stability of molten steel, and, combined with automatic control, will strongly promote the development of intelligent refining to achieve optimization of steelmaking and improve efficiency. Regarding promoting intelligent manufacturing in the steel industry, the LF refining process model is no longer limited to the establishment and deployment of single-function models and has begun to develop in the direction of integration, automation, and intelligence while its function has also changed from a single prediction and recommendation to overall intelligent control and decision-making. LF process control and decision models are mostly single-function models, but few integrate applications. Due to the complexity and uncertainty of the refining process, these models have differences in stability and accuracy. Therefore, establishing an integrated model, standardizing the field process, improving the data quality, and combining automatic control and closed-loop feedback to further realize the intelligent control model have become important directions for future research and application of LF control models. Herein, the development and research status of LF refining control and decision models are summarized, including the alloying model, slagging model, temperature model, argon blowing control model, calcium treatment model, and other single-function models, as well as intelligent refining technology. The modeling principles and functions of these models are systematically reviewed, and future development directions of LF process intelligent control and decision models are prospected, providing a reference for the subsequent development and application of LF intelligent refining technology. The establishment and real landing of LF intelligent control and decision models not only require the realization and linkage of process control and decision models but also propose higher requirements for iron and steel enterprises. The realization of LF intelligent control and decision-making models can greatly improve the consistency and qualified rate of product quality, reduce energy consumption and cost, reduce manual intervention, and shorten the smelting cycle, thus improving the competitiveness of enterprises. With the continuous upgrading and improvement of model design, automation technology, and steel mill site environment, the application and development of LF intelligent control and decision-making models show great potential in realizing green, low-carbon, and intelligent manufacturing and would make great contributions to the progress and transformation and upgrading of the steel industry in the future.