Thermal gradients generated during the additive manufacturing (AM) build process cause residual stress and deformation (i.e., distortions) in thin-wall structures. These distortions pose significant challenges for part qualification and certification, particularly in thin-walled components, due to the resulting dimensional inaccuracies and compromised structural integrity. To address these issues, part-scale simulations using the inherent-strain technique have been developed to predict distortions [1] and have been shown to be an effective approach. For example, previous work by the authors demonstrated success in distortion prediction for thin-walled 316L stainless steel parts [2], but the method was limited to this material. In this study, we outline the calibration process and validation efforts for applying the inherent strain method to predict distortion in various as-built printed thin-wall geometries of Ti-6Al-4V (Ti64). Calibration is performed using a thin-walled house geometry, followed by predictions on corrugated sheet and cylindrical geometries. The successful calibration and validation of this method provide a foundation for improving distortion prediction accuracy in Ti64 thin-walled components, supporting the design and optimization of metal additive manufacturing parts for this material. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. [1] W, Dong, X. Liang, Q. Chen, S. Hinnebusch, Z. Zhou, A. To. A new procedure for implementing the modified inherent strain method with improved accuracy in predicting both residual stress and deformation for laser powder bed fusion. Additive Manufacturing, Vol. 47, 2021. [2] C. Herriott, M. Stender, B. White, C. Crandall, S. Shinde, et al., Distortion compensation for metal additive manufacturing: verification, validation, and development of a thermal mechanical workflow, SAND2024-09416C (2024).