We use a database of approximately 200,000 modified Mercalli intensity (MMI) observations of California earthquakes collected from USGS "Did You Feel It?" (DYFI) reports, along with a comparable number of peak ground-motion amplitudes from California seismic networks, to develop probabilistic relationships between MMI and peak ground velocity (PGV), peak ground acceleration (PGA), and 0.3-s, 1-s, and 3-s 5% damped pseudospectral acceleration (PSA). After associating each ground-motion observation with an MMI computed from all the DYFI responses within 2 km of the observation, we derived a joint probability distribution between MMI and ground motion. We then derived reversible relationships between MMI and each ground-motion parameter by using a total least squares regression to fit a bilinear function to the median of the stacked probability distributions. Among the relationships, the fit to peak ground velocity has the smallest errors, though linear combinations of PGA and PGV give nominally better results. We also find that magnitude and distance terms reduce the overall residuals and are justifiable on an information theoretic basis. For intensities MMI≥5, our results are in close agreement with the relations of Wald, Quitoriano, Heaton, and Kanamori (1999); for lower intensities, our results fall midway between Wald, Quitoriano, Heaton, and Kanamori (1999) and those of Atkinson and Kaka (2007). The earthquakes in the study ranged in magnitude from 3.0 to 7.3, and the distances ranged from less than a kilometer to about 400 km from the source.