We use Global Positioning System (GPS) velocities and stress orientations inferred from seismicity to invert for the distribution of slip on faults in the southern California plate-boundary region. Of particular interest is how long-term slip rates are partitioned between the Indio segment of the San Andreas fault (SAF), the San Jacinto fault (SJF) and the San Bernardino segment of the SAE We use two new sets of constraints to address this problem. The first is geodetic velocities from the Southern California Earthquake Center's (SCEC) Crustal Motion Map (version 3 by Shen et al.), which includes significantly more data than previous models. The second is a regional model of stress-field orientations at seismogenic depths, as determined from earthquake focal mechanisms. While GPS data have been used in similar studies before, this is the first application of stress-field observations to this problem. We construct a simplified model of the southern California fault system, and estimate the interseismic surface velocities using a backslip approach with purely elastic strain accumulation, following Meade et al. In addition, we model the stress orientations at seismogenic depths, assuming that crustal stress results from the loading of active faults. The geodetically derived stressing rates are found to be aligned with the stress orientations from seismicity. We therefore proceed to invert simultaneously GPS and stress observations for slip rates of the faults in our network. We find that the regional patterns of crustal deformation as imaged by both data sets can be explained by our model, and that joint inversions lead to better constrained slip rates. In our preferred model, the SJF accommodates ???15 mm yr-1 and the Indio segment of the SAF ???23 mm yr-1 of right-lateral motion, accompanied by a low slip rate on the San Bernardino segment of the SAF 'Anomalous' fault segments such as around the 1992 Mw = 7.3 Landers surface rupture can be detected. There, observed stresses deviate strongly from the long-term loading as predicted by our simple model. Evaluation of model misfits together with information from palaeoseismology may provide further insights into the time dependence of strain accumulation along the San Andreas system. ?? 2004 RAS.