Many tree species and worldwide forests do not have updated local allometry. They call for the development and application of local allometry. However, there are a great number of allometric equations reported for worldwide species with a major emphasis on temperate North American and European tree species. Available equations can be classified by the way equation parameters are estimated as empirical, theoretical and semi-empirical non destructive methods of tree M assessment. Empirical models commonly calculate statistical coefficients by least square techniques in linear, log-linear, non-linear, multiple linear and non-linear, seemingly unrelated linear and non-linear and exponential mathematical formats where diameter at breast height or basal diameter, top height, canopy area and wood specific gravity are independent variables that individually or in combination explain tree M of harvested trees. Conventional mathematical allometric models have intrinsic variations larger than 20% of the tree M but new empirical equations that contain H and ρw as independent variables, in addition to the conventional normal diameter, are improving tree M evaluations since the intrinsic error has been reduced to 16%. Theoretical and semiempirical non-destructive methods are in the early stages of development and require further testing and refinement although they can be preliminarily recommended as nondestructive approaches of tree and stand M computation. In spite of the wealth on biomass allometry for several trees and forests, conventional plot M evaluations exhibit variations as large as two orders of magnitude when contrasting on and off-site equations. One potential procedure to reduce uncertainty is combining the conventional empirical, semi-empirical non-destructive, and restrictive methods to improve precision when computing tree and plot M for forests that do not convey local biomass allometry. However, research on understanding variations by coupling these methods are lacking elsewhere. There is a variety of interpolation techniques of tree or plot M to forests, regional and national scales but they display variations close to three orders of magnitude when assessing AGB stocks. Coupling tree allometry with FIA evaluations, environmental gradient analysis and remote sensing techniques may reduce this variation in future AGB studies. Modern remote tree data collection techniques (LIDAR) combined with empirical, locally-derived functions to estimate timber volume as a function of diameter and canopy height and canopy height as a function of diameter plugged into the non-destructive semi-empirical, shape-dimensional analysis model could improve AGB evaluations at the spatial scale of interest.