Building energy and Carbon emission calculation methods for regions are of limited use if appropriate input data cannot be economically generated. To enable a wider uptake of regional modelling methods an automated analysis system is required to replace or assist time-consuming and expensive manual surveys of building stock. Building age is an important parameter in estimating energy use and Carbon emissions. In this paper a number of methods to extract information about the built environment from digital maps and use that information to infer building age have been tested against a database of a known large urban region. The methods include different types of shape recognition of plan form and of identification of contextual geography; e.g. distance from entrance to the nearest road. Tested against samples containing several thousands of domestic buildings from a known region, it was found that the different methods were able to cluster buildings into different form “styles”, and that those styles had some correlation to built age. Victorian (pre-1919) age housing was detected with the greatest accuracy, with over 90% in the sample tested correctly identified. This is useful as those older buildings are often the least energy efficient. Success in identification of other eras was less pronounced; although the results are promising, further development of the methods are required.