Industrial Engineering, Innovation, and Machine Learning have continuously solved various problems in the world of Supply Chain Management. With large datasets, mathematical modelling, computational power, and excellence, Machine Learning is an excellent predictive tool than can help build resilient, gritty, robust environments that can enhance the global environment and solve cost minimization problems. Better modelling and data mean better approximation strategies. Hence, 21^st Century various challenges can be modelled and solved with Machine Learning and Innovation. This paper explores important concepts in a technology that can handle challenges in the world through cutting edge datasets, algorithms, innovative toolbox, and transformative impacts in the Australian Supply Chain for the make benefit of the planet. Innovative solutions can be used to enhance operational efficiency, analytics, and implementation barriers that have challenged IEs in the past due to lack of data. Through substantial value adding metrics, IE’s can drive the Australian market forward for continuous growth. From Government, Private Corporations, and NGO’s, IEs have the skills to add value to many businesses. In Australia, IEs are capable of predicting many variables through an accurate mathematical toolbox, Machine Learning blueprint, and innovation that have helped handle variances in the Australian Supply Chain. With abundance of data, value adding is an IE mission that is possible thanks to Machine Learning and Innovation.