The debate between the trait- and state-theories of wisdom has always been a heated topic. The trait-theory of wisdom argues that wisdom is a stable personality trait that is difficult to be intervened through self-improvement or external efforts, and only the sages possess "true wisdom". Empirical studies basing on the trait theory have utilized self-report measurements and the nomination method. However, their theoretical basis and research methodology have two shortcomings: (1) The excessive pursuit of the "pure" trait-level of wisdom leads to the "utopia of wisdom"; (2) self-report measurements have inherent defects. The state-theory of wisdom holds that wisdom is not always a stable and invariable quality, but a state of mind that changes with the situation. Wisdom can be increased through one's efforts and external assistance. This theory inspires studies on wisdom intervention. In recent years, a considerable number of empirical studies have been conducted basing on the state-theory of wisdom, suggesting that wisdom is not an unattainable quality that only the sages can possess. Research of wisdom basing on the state-theory incorporates self-report, text analyses, event reconstruction, narrative analysis, and other state-of-art technologies. These studies are truly mixed-method studies, integrating qualitative and quantitative methodologies. Inspired by the density distribution theory of personality proposed by Fleeson (2001), Grossmann, Gerlach, et al., (2016) drew attention to the density distribution theory for studies of wisdom. They believe that wisdom could be defined as the density distribution of wise behaviors in specific contexts, and individuals show different levels of wisdom (trait expression) basing on situations (state expression). The traits of wisdom can be construed as the distribution of state expressions in specific situations. However, there is still space for improvement for the density distribution model. The shape of the distribution can be further specified, and distinctions can be made between people with different levels of wisdom. Given these issues, we put forward a new theoretical model: the trait-state normal distribution model. In this model, we try to categorize people into three groups (the high-level, medium-level, and low-level wisdom). According to the central limit theorem in statistics, we propose that trait-levels of wisdom are reflected through the mean levels of wisdom performances across different states, and the distributions of the mean level of wisdom among people fit the normal distribution. This new model attempts to integrate trait differences between individuals and state fluctuations within individuals, reflecting the individual wisdom accurately and objectively. Future studies should test this theoretical model empirically using the signal detection theory, longitudinal tracking, etc. Delineating the trait and state theories of wisdom facilitate further understanding of the concept of wisdom, and provides an important theoretical basis for wisdom fostering. Future studies should focus on the improvement of measurement methods of wisdom, the moderating effect of the importance of life problems on the stability of wisdom, and the cultural effects on the views of wisdom, which could then affect the fluctuation of wisdom in real life. Finally, the application of hybrid methods (e.g., Experience-sampling Methodology and Aggregation technology) is important for integrating trait- and state- theories of wisdom.