No matter the United Nation 2030 Sustainable Development Goals or China's ecological civilization construction, the ultimate goal is to coordinate the relationships between human and nature, so as to sustain the provision of ecosystem goods and services to improve human well-being. During the past two decades, as ecosystem service research becomes the frontier and hotspot, there has been more and more attention paid to the linkages between ecosystem services and human well-being. To quantify their linkages, the premise is to establish corresponding index systems to quantify ecosystem services and human well-being, respectively. Nevertheless, the majority of current research focuses on ecosystem service assessment, there are relatively less studies on human well-being assessment that is compatible to the ecosystem service framework. Therefore, it is urgently needed to provide a set of methodologies for developing human well-being indices taking the linkages between ecosystem services and human well-being into consideration. Based on many years' theoretic analyses and practices, we synthesized the theoretic bases and methodologies for human well-being assessment. We compared the advantages and disadvantages of different methods. We recommend the improved factor analysis approach for five main reasons. First, the improved factor analysis approach provides a general and pragmatic composite index development method that combines the theoretic design with data mining technique, which largely improves the internal and external consistency of developed human well-being index system. Second, the improved factor analysis approach is scale free (e.g., from household, township, to county and national levels) and can also be applied to different conceptual framework. This is particularly useful to design studies under different ecological and socioeconomic contexts. Thirdly, the improved factor analysis approach is flexible for weighting setting. The weighting can be generated by data variation or be customized by management goals. Fourthly, the improved factor analysis approach does not have the measurement error free assumption and is more robust, especially for secondary data. Considering it is often time consuming and costly to collect first hand data, such advantage makes it is possible to develop effective human well-being indices based on secondary data (e.g., statistical yearbook data). Finally, the improved factor analysis approach produces a composite index system, which includes the overall index and sub-indices. Such index system can be used both for analyzing large-scale spatiotemporal dynamics and small-scale detailed linkages between different ecosystem services and various dimensions of human well-being. We hope that our synthesis will lay a foundation for the quantification of linkages between ecosystem services and human well-being.