We present a Bayesian approach for modeling a time series for a cumulative record that takes the form of the maximum or minimum of a sequence of attempts, in the absence of data for the underlying attempts. We discuss the derivation of the likelihood function, sampling of the posterior via PyMC3, and forecasting the distribution of future records.