The World Happiness Report is released every year on 20th March on the occasion of World Happiness Day. The 2023 World Happiness Report has provided detailed study of happiness trends in over 150 countries. The happiness index and growth of any nation have the interplay of psychological, economic, and social factors. Understanding this correlation can provide insight into how to design effective policies to promote the economic and psychological growth of the people of the nation. This research problem focuses on providing an ML model that can predict the happiness index based on features like social hold-up, liberty to make life choices, gross domestic product GDP per person, healthy life longevity, generosity, and perceptions of exploitation. This research is useful to the government sectors to take corrective actions to increase the well-being of the people of the nations. This research is also helpful to private organizations and NGOs in deciding further actions for the development of nations. This research paper can also help individual researchers to gain insights into applied machine learning concepts to resolve real-life problems. We have applied ML algorithms to achieve the research objective of predicting the happiness index by applying Support Vector Regression, Random Forest, Decision Tree, Cat- Boost & Linear Regression ML algorithms. The best generated ML models after experimentations are: SVR with the highest R2 value of 0.827 and the Decision tree has achieved the highest accuracy with minimum prediction errors in Mean Absolute Error of 0.364 while Mean Square Error of 0.233 and Root Mean Square value of 0.483 respectively which makes them suitable for the prediction of global Happiness index.