Climate change associated with increasing concentrations of the greenhouse gas, carbon dioxide(CO2), is expected to lead to an increase in global mean temperature of between 1 and 3.5 deg C by the end of the 21st century, with regional changes in rainfall and humidity. This thesis is concerned with modelling the effects of a changing climate and atmospheric C02 concentration on global vegetation. The process-based model, DOLY (Dynamic glObal phtogeographY), is used. It is able to operate using three climate variables, two soil variables and an atmospheric CO2 concentration. Its outputs are leaf area index (LAI), and net primary productivity (NPP). The LAI and NPP values predicted by DOLY were used to run a life-form model with a climate change scenario. It was found that warming led to the spread of trees into the tundra region. The DOLY model was also coupled with the Hadley Centre general circulation model to determine the feedbacks of vegetation on climate. With a global warming of 2◦C, the global feedback of vegetation on temperature was a decrease of 0.1 deg C. However at the regional scale the feedback was +/-2 ◦C, of similar magnitude to the driving temperature change. Finally, the DOLY model was run with transient climate data from the Hadley Centre. The boreal forest moved north, and the Gobi desert and the southern steppes in the former Soviet Union shrank in area. The sensitivity of the model to its soil and climate inputs have also been analysed over a range of environments and the model has been validated with reference to satellite data and experimental data. It was found to perform well. This thesis has shown that it is possible to predict current and possible future distributions of vegetation with climate change using a vegetation model.