<p>In emerging coating materials, iron-based amorphous alloys have garnered increasing scientific attention due to their exceptional mechanical properties. Thermal spraying is a primary method for fabricating iron-based amorphous coatings. However, the optimization of the spraying process for developing high-performance iron-based amorphous coatings using thermal spraying technology still faces many challenges. These challenges mainly arise from the complex multivariable and nonlinear interactions between spraying process parameters and the microstructure and phase structure characteristics of the coatings, which limit the enhancement of coating performances. This review summarizes recent advancements in the process optimization of thermal spraying for iron-based amorphous coatings. We introduce the current status of process optimization of three main thermal spraying methods—plasma spraying, flame spraying, and arc spraying—for preparing iron-based amorphous coatings, focusing on the effects of spraying parameters on coating porosity, mechanical properties, and corrosion resistance. Subsequently, this review discusses various methods for optimizing thermal spraying process parameters, including empirical statistical methods, numerical simulations, and machine learning, with a detailed analysis and comparison of their advantages and limitations. More importantly, the field currently lacks a unified framework to integrate traditional metallurgical knowledge with emerging data-driven approaches. Finally, the review outlines the future research directions of thermal spraying, emphasizing the integration of multi-scale sensor data streams and the application of real-time diagnostic-based adaptive control systems. These research directions will contribute to addressing the data-driven intelligent optimization needs of next-generation thermal spraying systems, a nexus underexplored in prior reviews despite its growing relevance to Industry 4.0-driven manufacturing paradigms.</p>