Laser beam welding (LBW), as a non‐contact process with short cycle times and small heat affected zone, is a key technology for automated metal fabrication. Despite its efficiency, the susceptibility of certain alloys to solidification cracks remains a significant challenge. These cracks emerge in the transition zone between liquid and solid phases during the solidification process. Thermo‐fluid dynamic processes within the melt pool play a crucial role in solidification crack formation during LBW, influencing heat distribution, mass transport, and consequently, the microstructure and mechanical properties of the weld. An in‐depth exploration of thermo‐fluid dynamics within the melt pool, contributes to an improved understanding of the correlations between process parameters and melt pool flow aiming to avoid solidification cracks. Therefore, in situ process investigations were conducted at beamline P07 of PETRA III at the German Electron and Synchrotron (DESY). 1.4404 stainless steel specimen containing an 5 wt.% of tungsten particles, serving as tracer, were additively manufactured using laser powder bed fusion. The tungsten particles are evenly distributed within the samples. High‐speed synchrotron x‐ray imaging of the process zone allowed for detailed in situ analyses. Leveraging the lower x‐ray absorption coefficients of the base steel material compared to tungsten, the particles appeared as dark dots in the images. The experimental setup involved blind welds on the samples, where a portion of the sample was melted by the laser beam, forming a molten pool in the center while the edges remained intact. The uniform distribution of the particles in the sample means that the movement of the particles in the molten pool is overlaid by static particles located in the unmelted edges of the sample. To enhance the observation and tracking of particle movement within the melt pool, the image contrast was optimized, and static particles were filtered out. The resulting images offer a visual representation of thermo‐fluid dynamical flows during LBW, based on the movement of tracer particles. Analysis was performed using an on Hessian blob detection and Kalman filter based tracking tool [1]. The results of this investigation provide valuable insights into the intricacies of thermo‐fluid dynamics during LBW, offering a foundation for the advancement of numerical modeling and simulation tools in the field of LBW.