Development of a complicated technical problem encompasses different successive decisions that are based on techical analysis and engineering judgment. In each of these steps, somedegree of non-determinism is inevitable. The paper discusses different types of non-deterministic parameters that may be relevant in different stages of engineering analysis. The entire cycle of development of a product is considered, and it is shown that the relevance of methods isdifferent in different stages of the development cycle. A classiﬁcation of different types of non-deterministic properties is presented. Based on the nature of these different classes of model properties, it is discussed to what degree each of these ﬁts in the framework of either a probabilistic or a non-probabilistic concept.The availability of realistic data in an appropriate format is another issue that should be taken into account. A validated probabilistic representation is usually only possible after an extensive campaign of data acquisition has been conducted, or at least after suffcient data have been collected to allow for a reliable estimation of a statistical model. A study of scientiﬁc literature shows that validated information is not always available. A general conclusion is that probabilistic methods are applicable in later stages of development, when a suffciently large database of product data has been gathered. Probabilistic approaches are perfectly suited for conditions when the product is already in service. Possibilistic analysis on the other hand is best suited for application in cases when the data set about the product at hand is still incomplete.