Readme: Supplementary Data: ML-Algorithm Source Code algorithm_predictive_modeling.py; https://doi.org/10.15480/882.8838 Welcome to the supplementary data file for the Source Code of the AI-Tool featured in our recent scientific paper: PREDICTIVE MODELING OF LATTICE STRUCTURE DESIGN FOR 316L STAINLESS STEEL USING MACHINE LEARNING IN THE L-PBF PROCESS [doi:10.2351/7.0001174]. This repository contains additional information and resources to enhance your understanding and utilization of the implemented artificial intelligence tool. About the AI-Tool Our AI-Tool is a solution developed to address the challenges outlined in our research paper titled �PREDICTIVE MODELING OF LATTICE STRUCTURE DESIGN FOR 316L STAINLESS STEEL USING MACHINE LEARNING IN THE L-PBF PROCESS". This tool leverages advanced machine learning techniques to predict the mechanical properties of infill structures based on their designed parameters. This can be used to identify the optimal infill structure geometry for a given set of mechanical requirements and loading conditions Citation If you find our AI-Tool useful for your research or project, we kindly ask that you cite our original scientific paper. The citation information is available in the paper. Contact For any questions, issues, or collaborations related to the AI-Tool or the cited paper, feel free to reach out to us via our contact email listed below. Thank you for your interest in our work. We hope this supplementary data enriches your experience and contributes to the advancement of your research. Karim Asami; Karim.Asami@tuhh.de https://orcid.org/0000-0001-8382-263X TUHH; iLAS: Institute for Laser and System Technologies Sebastian Roth; Sebastian.roth@tuhh.de https://orcid.org/0000-0002-3921-0959 TUHH; iLAS: Institute for Laser and System Technologies Dirk Herzog; Dirk.Herzog@tuhh.de https://orcid.org/0000-0001-7059-6151 TUHH; ISM: Institue for Industrialization of Smart Materials Tim R�ver; Tim.R�ver@tuhh.de https://orcid.org/0000-0002-3709-339X TUHH; iLAS: Institute for Laser and System Technologies Claus Emmelmann; C.Emmelmann@tuhh.de https://orcid.org/0009-0008-4698-2077 TUHH; iLAS: Institute for Laser and System Technologies Michel Krukenberg; TUHH; iLAS: Institute for Laser and System Technologies