Seismic source models, such as moment tensors and single forces, are essential for understanding source physics across types and scales, from laboratory experiments to large-scale ruptures. While the theoretical foundations are well-established, source estimates are limited by observational constraints, subsurface heterogeneity, and modeling assumptions that affect the reliability of results. This session highlights recent advances in seismic source estimation using both traditional and emerging methods. We welcome contributions that improve or propose new estimation strategies, particularly those focused on uncertainty quantification; integration of diverse datasets including local to regional arrays (sparse or dense), distributed acoustic sensing (DAS), infrasound, and geodetic measurements such as InSAR; and innovative approaches across applied and computational domains, including machine learning and other modeling approaches. We invite studies addressing seismic sources of any type or scale, including anthropogenic, tectonic, and volcanic processes.