A description of the Canada Land Capability Classification for forestry, and an analysis of data collected in the East Kootenay and Vanderhoof Districts of British Columbia were presented. A brief description of the climate, geology, physiography and soils in the East Kootenays was given. A description of the objectives of the land capability for forestry and a survey of the pertinent literature was included. The determination of Forest Land Productivity, and the accuracy of assigned productivity classes, were reviewed. It was found that the sources of error in productivity determinations included: (1) insufficient plots, (2) problems in defining 'normal' stocking, (3) extrapolation of MAI to a base of 100 years, (4) a strong tendency to select plots on northern aspects, and (5) the exclusion of plots on soils not representative of soil series descriptions. Two alternative methods for assigning productivity classes were discussed. They were point sampling and regression techniques. Both the point sampling and regression techniques gave results comparable to the conventional method, i.e. MAI determinations based on 1/5th acre plots, within prescribed constraints, and only in the interior of British Columbia. Results obtained from point samples on Vancouver Island were significantly different from those obtained on one-twentieth acre plots. The assignment of productivity subclasses was discussed. Here the only method presently feasible is a value judgement made by research workers. The results of the study revealed three areas where further research would result in a more accurate Forest Land Classification. These areas include: (1) the measurement of environmental factors which determine forest productivity, (2) the use of field and greenhouse experiments to establish methods for determining the relative effect of environmental influences in limiting tree growth, and (3) a more extensive study of the use of various sampling techniques to get a direct measure of productivity in terms of MAI. / Forestry, Faculty of / Graduate