This paper describes a protocol for a market of machine learning models. The economic interaction involves two types of agents: data providers- agents that have some data and want to use it to get a predictive model, and model providers- agents able to use the data to generate predictive models. First, we will show that the process is informationally asymmetric, therefore a standard direct market can not function. Then, we design a protocol with the aim of creating a viable and efficient market mechanism for these particular services, under the specific challenges of information asymmetries. The protocol is theoretically analysed, to establish it’s correctness and computational complexity. We also propose a simple reference implementation based on a HTTP API. The implementation is then used in a few case studies, and analysed empirically.