Predicting the crack propagation behavior in welded stiffened panels, which are often used in marine, civil, and aerospace structures, has been challenging. The presence of welded stiffeners creates complex stress conditions that need to be properly considered while predicting the crack growth. Another challenge is the presence of significant uncertainties, the variability in the mechanical properties of materials and geometric parameters are among the main contributors to these uncertainties. In this context, accurate quantification of uncertainties associated with these parameters is crucial for the accurate prediction of the fatigue service life and for ensuring structural integrity and operational reliability throughout the service life. This paper conducts a sensitivity analysis to evaluate the effect of relevant input parameters, covering geometric and mechanical properties, on crack propagation behavior. The geometric parameters include the main panel thickness and stiffener characteristics while the mechanical properties cover the crack propagation regression parameters, modulus of elasticity, and yield strength. Furthermore, the effect of the geometric uncertainties on the fatigue reliability of these panels is also quantified. A 3-D finite element analysis, an artificial neural network, and an elastic-plastic crack growth model are integrated to predict crack propagation under cyclic loading. The sensitivity and reliability assessment approach is illustrated on stiffened panels with T- and L-shape stiffeners subjected to axial tensile fatigue loading. The proposed approach is validated using experimental test data reported in literature.