Owing to its relevance to remotely-sensed imagery of landscapes, this paper investigates the ability to infer diameter at breast height (DBH) for five species of Australian native 'Eucalyptus' from measurements of tree height and crown projection area. In this study regression models were developed for both single trees and clusters from 2 to 27 stems (maximum density 536 stems per ha) of 'Eucalyptus bridgesiana', 'Eucalyptus caliginosa', 'Eucalyptus blakelyi', 'Eucalyptus viminalis', and 'Eucalyptus melliodora'. Crown projection area and tree height were strongly correlated for single trees, and the log-transformed crown projection area explained the most variance in DBH (R² = 0.68, mean prediction error ±16 cm). Including tree height as a descriptor did not significantly alter the model performance and is a viable alternative to using crown projection area. The total crown projection area of tree clusters explained only 34% of the variance in the total (sum of) the DBH within the clusters. However average crown projection area per stem of entire tree clusters explained 67% of the variance in the average (per stem) DBH of the constituent trees with a mean prediction error ±8 cm. Both the single tree and tree cluster models were statistically similar and a combined model to predict average stem DBH yielded R² = 0.71 with a mean prediction error (average DBH per stem) of ±13 cm within the range of 0.28-0.84 m. A single model to infer DBH for both single trees and clusters comprising up to 27 stems offers a pathway for using remote sensing to infer DBH provided a means of determining the number of stems within cluster boundaries is included.