  The concept of 'Stateless Ethereum' was conceived with the primary aim of
mitigating Ethereum's unbounded state growth. The key facilitator of Stateless
Ethereum is through the introduction of 'witnesses' into the ecosystem. The
changes and potential consequences that these additional data packets pose on
the network need to be identified and analysed to ensure that the Ethereum
ecosystem can continue operating securely and efficiently. In this paper we
propose a Bayesian Network model, a probabilistic graphical modelling approach,
to capture the key factors and their interactions in Ethereum mainnet, the
public Ethereum blockchain, focussing on the changes being introduced by
Stateless Ethereum to estimate the health of the resulting Ethereum ecosystem.
We use a mixture of empirical data and expert knowledge, where data are
unavailable, to quantify the model. Based on the data and expert knowledge
available to use at the time of modelling, the Ethereum ecosystem is expected
to remain healthy following the introduction of Stateless Ethereum.
