Highly iterative product development is a promising approach, which enables a continuous inclusion of customers in the product development process. A stronger involvement of customers results in more frequent changes of the required product characteristics while the product is being developed. For the planning of manufacturing technologies, which takes place in parallel to product development, this means that very uncertain product and technology information have to be processed. In order to consider these uncertainties when designing technology chains, technology planners have to be able to model and quantify them. Moreover, due to the frequent product changes during the highly iterative development process, an evaluation of how capable manufacturing technologies are for handling future changes of product characteristics is essential for technology planners. This paper presents a new methodology, which enables the evaluation of manufacturing technologies regarding their capability to react to future product changes within the development process. Firstly, a new method based on fuzzy sets and the Dempster-Shafer theory of evidence is presented. It allows an aggregation of uncertain product and technology information from different sources. Afterwards, the influences of manufacturing technologies within a technology chain on the product characteristics are modeled considering the different uncertainties. Finally, a new method to evaluate the capability of manufacturing technologies to cope with future product changes is introduced. This allows technology planners to predict the capability of manufacturing technologies to manufacture the future, fully developed product and hence to identify alternatives to reduce the information uncertainties, for example by executing prototype experiments.