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Tree aboveground biomass (e.g., bole, branches, and foliage), <i>M</i>, plays key roles in forest management as it is the basis for evaluating the sink and flux of, for example, carbon and nitrogen, stand productivity, dendro-energy, litter & root biomass, hydrological parameters, among others. With the aim of further simplifying and understanding <i>M</i>, the central objective of this research was to review available techniques to develop, test, and validate two independent novel non-destructive, semi-empirical models using four major <i>M</i> datasets: (i) the shape dimensional bio-physical, <i>M_SD</i>; and (ii) the restrictive mathematical, <i>M_NR</i>, models. The proposed models advance and test how each of both approaches: (i) constant or (ii) variable scalar coefficients perform when predicting <i>M</i> with major assumptions bearing bio-physical principles. Results showed that <i>M</i> has to be predicted eventually with variable scalar coefficients; both models predicted compatible <i>M</i> figures; the evaluations matched the conventional equation well; and the independent data sets were well validated; the coefficients of determination, r², and the standard errors, Sx%, had values >96% and <20%, respectively, for most tested conifer tree species. In spite of demonstrating empirically and physically the ontogenetic-dependency of scalar coefficients, the <i>M_NR</i> model, with constant <i>β</i>-scalar and variable <i>a</i>-intercept coefficients, performed slightly better, and precision appeared to be a function of the tree species growing in different forest ecosystems. Therefore, better parameterization advances for the testing and validation of the <i>M_SD</i> model that uses variable scalar coefficients, which are consistent with ontogenetic principles, are preliminarily recommended for <i>M</i> assessments. The updated revision of models, the independent development, the construction using different assumptions, the individual mathematical and bio-physical parameterization, the consistency on <i>M</i> assessments, and the bearing of physical and biological properties are key pieces of scientific information presented in this report are required in modern forest management when predicting <i>M</i> and associated variables and attributes.