The integration of graphene into Ti-6Al-4V alloys via Selective Laser Melting (SLM) presents a promising pathway to enhance the mechanical and functional properties of metal matrix composites. However, achieving uniform dispersion remains a challenge due to graphene agglomeration in the base material. This study introduces an Agglomeration Factor (AF) as a quantitative metric to assess graphene clustering as a result of variation in laser power during the SLM process. In this study, a hybrid methodology is used, which combines Multiscale Multiphysics Simulation Modeling (MMSM) using Ansys, with experimental validation through SEM-based image analysis. Five specimens were simulated and fabricated using laser powers of 200, 250, 300, 350, and 400 W, respectively, while maintaining all other process parameters, including scanning speed and powder bed temperature, constant. Results demonstrated a strong inverse correlation between laser power and AF in both experimental and simulated environments, with the lowest AF observed at 400 W, which indicates optimal dispersion. While the highest AF was observed at 200 W. This demonstrates that an increase in laser power, translates in improved graphene dispersion in the Ti-6Al-4V matrix. Furthermore, it was observed that the MMSM’s predictive accuracy deviates from experimentation by 5.71%. This study establishes AF as a reliable dispersion metric and demonstrates the critical role of laser power in mitigating graphene clustering. This study provides a framework for optimizing SLM-based nanocomposite fabrication.