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• BALM is an important indicator that could be used to enhance cohort balance in forests. • BALM estimation at smaller plot sizes and sample sizes is unstable. • Stabilization of BALM starts at the plot size 6 m radius and sample size 6 trees. • The optimal plot size and sample size are 380–615 m2 and 50–80 trees, respectively. • ALS point density of at least 5 points m−2 is required for reliable BALM estimation. Airborne laser scanning (ALS) assisted basal area larger than mean (BALM) estimation measures the cohort balance in forests and provides adequate opportunities to describe forest structure. However, a problem still exists that how the plot size, sample size (number of trees), and ALS point density affect the BALM estimation. We tackled this question by using both field and ALS data from a typical managed boreal forest area in Finland. Various concentric circular plots (1–15 m radii) were simulated within the actual field plots (squared) and the optimal plot size and sample size were selected by observing changes in the absolute correlation between BALM estimates and various ALS metrics. Instability in the correlation was found at the smaller concentric circular plots (1–5 m radii) and sample sizes (less than 6 trees) but as the plot size and sample size increased, the correlation followed a convex curve. The maximum correlation was found between a concentric circular plot size 11–14 m radii (380–615 m2 area) and sample size 50–80 trees which could be the optimal plot size and sample size for a reliable BALM estimation. With regards to the ALS point density, no major effects were observed on the relationship between BALM estimates and various ALS metrics unless the point density is less than at least 5 points m−2. The point density of the current nationwide ALS survey is matching the minimum point density requirement obtained in this study and thus it is suitable for a reliable forest structural assessment. [ABSTRACT FROM AUTHOR]