## 1 Introduction
This framework considers life satisfaction to be multifaceted, built with material (jobs and earnings, income and wealth, and housing conditions) and nonmaterial components (work-life balance, education and skills, health status, civic engagement, social connections, environmental \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & **CQL** & **IWBUS** & **CIW** & **QL** & **CGWBI** & **GNH** & **WHI** & **HPI** & **BLI** \\ \hline Income (I) & \(\surd\) & \(\surd\) & \(\surd\) & & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ Education (ED) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & & \(\surd\) \\ Health (H) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ Environment (E) & & & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ Housing (H) & \(\surd\) & & & \(\surd\) & \(\surd\) & & & \(\surd\) \\ Time use (T) & \(\surd\) & & \(\surd\) & \(\surd\) & & & & \(\surd\) \\ Jobs (J) & \(\surd\) & & & \(\surd\) & \(\surd\) & & & & \(\surd\) \\ Community (C) & & & \(\surd\) & & \(\surd\) & \(\surd\) & \(\surd\) & & \(\surd\) \\ Governance (G) & \(\surd\) & & \(\surd\) & \(\surd\) & & \(\surd\) & & \(\surd\) \\ Generosity (G) & & & & & & & & \(\surd\) \\ State of IQ & & \(\surd\) & & & & & & & \\ Safety (S) & \(\surd\) & \(\surd\) & & \(\surd\) & \(\surd\) & & & & \(\surd\) \\ Choices freedom (C) & & \(\surd\) & & & & \(\surd\) & \(\surd\) & & \(\surd\) \\ Life Satisfaction (L) & \(\surd\) & \(\surd\) & \(\surd\) & & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ No. of Dimensions & 9 & 7 & 8 & 7 & 9 & 9 & 7 & 4 & 11 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Various dimensions of quality of life indicators. quality, governance subjective well-being, and personal security). Moreover, the system stresses the significance of evaluating the major assets that steer well-being over time, which should be cautiously supervised and administered to attain viable well-being. The resources can be evaluated through natural, social, human, and economic capital [16]. The OECD Better Life Index (BLI) consists of 11 subjects--jobs (J), housing (H), income (I), education (ED), community (C), governance (G), health (H), environment (E), safety (S), life satisfaction (L), work-life balance (W)--that are recognized as significant, in terms of of quality of lifestyles and material living conditions, for examining well-being throughout different countries [17]. The index is a combined index that cumulates a country's well-being conclusions using the weights stated by online end users. It envisages and weighs against some of the key features--housing, education, environment--that add to well-being in OECD countries. Using averaging and normalization, 20 sub-indicators were added to these main indicators. By selecting a weight for each sub-indicator, a user can rank countries according to their weighted sum. Figure 1 depicts the user rating of different well-being dimensions of 743,761 BLI users living within the OECD area [18]. The ratings concluded that all dimensions of quality of life are generally considered to be significant; nevertheless, education, health and life satisfaction dimensions are ranked higher. The lower ranked dimensions include community and civic engagement. Recent studies of several organizations throughout the world demonstrate the connection between prosperity and growth of societies, targeting sustainability and QOL. A place with high-quality living has more jobs opportunities. Natives are not willing to spend in places where there is not a good quality of life. The present study was the first step towards predicting life satisfaction scores using a machine-learning model. It could affect the survival of future generations and further aid the immigration process. The goal of the study was to predict the life satisfaction score of a country based on various key factors contributing to quality of life using machine-learning stack-based ensemble models.