This Special Issue presents eight original research articles and one comprehensive review addressing key challenges and innovative developments in additive manufacturing (AM) of metallic materials. Focused on both fundamental process understanding and applied outcomes, the articles explore optimization of laser-based AM techniques such as powder bed fusion and directed energy deposition, improvements in microstructure prediction and control, and the influence of process parameters on mechanical performance. The contributions include data-driven optimization approaches, process-structure prediction strategies, surface roughness analysis, fatigue behavior investigations, customized biomedical and industrial components, and topology-optimized designs for enhanced functionality of additively manufactured metallic parts. By combining new experimental findings, modeling approaches, and post-processing strategies, this Special Issue highlights recent progress in improving process reliability, part integrity, and application-specific performance. Intended for researchers, engineers, and professionals working in metal additive manufacturing and related fields, this collection serves as a valuable resource for advancing both scientific understanding and practical implementation of additive manufacturing technologies.