The systems and regulations that control human behaviour are the main emphasis of HRM. Finding the greatest talent from around the world, training them, evaluating their performance, rewarding them, and creating a positive work atmosphere are all part of the HRM field's magnificent duty. Developing a framework that accurately forecasts the need for talent and workforce skills becomes crucial because every organization's strategy depends, in part or in full, on its skill sets. When the human resource data is accessed for study of the higher cognitive processes involved, a variety of techniques may be used to extract the most useful information from the dataset. A common strategy for using data to inform decisions is data processing. On the other side, “state-of-the-art accuracy” in decisions is what predictive analytics is known for. The goal of this study is to provide a strategic decision-making model for “human resource management (HRM).” The study develops a decision-making framework based on data processing and predictive analytics for decisions pertaining to human resources. Given that HRM has a significant impact on an organization's longevity and efficacy, the model was created for global corporations. The suggested approach will be useful in enhancing HR systems’ effectiveness, which could have a favourable impact on business results.