The elastocaloric effect in functionally graded (FG) shape memory alloys (SMAs) offers a promising pathway to enhance the coefficient of performance (COP) in active regenerators for elastocaloric cooling applications. Our prior work demonstrated that FG SMAs with tailored variations in transformation temperature can significantly improve material efficiency. However, achieving precise control over transformation temperature during fabrication via additive manufacturing remains a critical challenge. This study focuses on predicting the process parameters required to achieve desired transformation temperatures in NiTi, NiTiHf, and NiTiCu SMAs. Leveraging a comprehensive dataset compiled from our group’s previous experiments and existing literature, we employ correlation analysis to establish relationships between process parameters and transformation temperatures. Our methodology includes constructing a Pearson correlation matrix to identify key parameter influences, comparing predicted versus actual transformation temperatures, and utilizing regression coefficients to propose actionable parameter adjustments. These predictive models aim to guide the additive manufacturing process, enabling the fabrication of FG SMA components with optimized transformation temperature profiles for enhanced elastocaloric cooling performance. This work provides a framework for bridging process-property relationships, advancing the practical implementation of SMA-based cooling technologies. REFERENCES [1] Saeedeh Vanaei, Shiva Mohajerani, Pete Rocco, Mahyar Sojoodi, Mohammad Pourshams, and Mohammad Elahinia, Advancing elastocaloric effect through additive manufacturing of NiTi shape memory alloys, Shape Memory and Superelasticity, submitted, (2024) [2] Shiva Mohajerani, Saeedeh Vanaei, Jaka Tusek, and Mohammad Elahinia, Enhancing Elastocaloric Regenerative Performance Using Functionally Graded Structures: A Model-Based Efficiency Evaluation, to be submitted, (2025) [3] Shiva Mohajerani, Alireza Behvar, Jaka Tusek, Ahu Celebi, and Mohammad Elahinia, Enhancing Elastocaloric Effect of Niti-X Through Functionally Graded Structures: A energy-based modeling, Abstract submitted to ASME SMASIS, (2025)