Abstract: Multi-component model engineering is described, for example, to model multi-component dynamical systems in which the true underlying processes are incompletely understood such as the Earth's biosphere, whole organisms, biological cells, the immune system, and anthropogenic systems such as agricultural systems, and economic systems. In an embodiment individual component models are linked together and associated with empirical data observed from the system being modeled in a consistent, repeatable manner. For example, a model component, its links with data, its outputs, and its links with other model components, are specified in a format to be passed directly to inference routines which use an inference engine to infer the most likely parameters of the multi-component model given subsets of the empirical data. The inferred parameter values take the form of a probability distribution representing the degree of uncertainty in most likely parameter.