The assessment of information relating to the spatial patterns of individual trees is becoming an increasingly important aspect of forest research and practical forestry. Numerous methods have been proposed over the years, with foresters preferring rapid methods able to provide statistically confident information. The Mean of Angles is one of the simplest of these methods. It is applicable for revealing complete spatial randomness (CSR) or the presence of clustering or regularity. We have tested the potential of the arithmetic mean of angles to serve as a practical measure of the degree of regularity or clustering. This study was conducted by applying random point sampling in various simulated theoretical point populations. The Mean of Angles method deserves consideration as a practical option for examining the spatial patterns of trees in forests. We suggest that the arithmetic mean of angles cannot be completely relied upon for indexing spatial patterns, but this deficiency can be overcome by examining the frequency distributions of angular measurements.