This study investigates the water plumes of Saturn's moon, Enceladus, using Direct Simulation Monte Carlo (DSMC) modeling to analyze venting dynamics and plume structures. Building on prior research, we employ a parametrized DSMC approach to model water vapor and ice particle flows, leveraging Cassini spacecraft data from instruments such as the Ion and Neutral Mass Spectrometer and the Ultraviolet Imaging Spectrograph. The study explores whether vent conditions, such as mass flow rates, mixture temperatures, and particle sizes, can be inferred from observational data. We develop a computational framework to expand plume simulations beyond 10 km altitudes, incorporating gravitational and inertial forces in an Enceladus-fixed reference frame. A sensitivity analysis correlates vent parameters with observed data, identifying critical contributors such as vent orientation and location, mass flow rate, exit temperature, and ice grain characteristics. This approach reduces the dimensionality of fitting procedures, enabling robust parameter constraints and a more detailed understanding of plume dynamics. Key findings include constrained values for mass flow rates, ice grain radii assuming single-size particles, and exit temperatures (∼44–61 K), consistent with theoretical predictions. Additionally, variations in vent orientation and positional parameters were refined from the work of Porco et al. (2014, https://doi.org/10.1088/0004-6256/148/3/45). These results highlight the importance of collision dynamics in shaping plume structures. This work establishes a computationally efficient methodology for analyzing cryovolcanic plumes applicable to future missions exploring icy moons such as Enceladus or Europa. By prioritizing sensitive parameters, the study offers insights for optimizing observational strategies to maximize scientific yield.