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

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... 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.