Isogrid structures offer an excellent balance between mass and rigidity, making them a crucial component in various industrial sectors. However, like all types of structures, isogrids are susceptible to performance degradation due to uncertainties in geometrical and material parameters arising from manufacturing errors and exposure to critical service environments. This paper addresses the effects of parameter uncertainty on the structural behavior of isogrid tube structures. To this end, a Sobol index is employed to assess the sensitivity of the tube’s natural frequency, axial buckling, torsional buckling, and overall mass to three geometrical and one material parameter, each subject to a 10% random variation. The data for this analysis were generated using a parametrized numerical model specifically developed for this purpose. To optimize computational costs further, an artificial neural network predictive model is proposed, which accurately replicates the behavior of the numerical model. The results indicate that the angle between helicoidal ribs is the most influential parameter.