Additive manufacturing (AM) is emerging as an alternative to traditional subtractive methods. However, AM technologies face challenges such as high production costs, slow speeds, and lower strength values. Among the key parameters influencing both product strength and production costs, printing speed plays a crucial role. In this study, an experimental dataset of fifty samples, generated using a full factorial design with PLA material, was used to examine the effects of input printing parameters on mechanical characteristics and build time. Correlation analysis revealed significant relationships between the variables. Therefore, Monte Carlo simulations were applied to quantify the impact of uncertainties in filling velocity on critical output metrics. The probabilistic analysis, conducted under 5% and 10% uncertainty levels, provided insights into the variability of tensile strength, surface roughness, and build time. The results show that variations in input parameters significantly affect output metrics, offering valuable insights for optimizing 3D printing parameters and improving system reliability.