This report summarizes the results of an analysis of the safety performance of Oregon’s intersections. Following a pilot study, a database of 500 intersections randomly sampled from around the state of Oregon in both urban and rural environments was assembled. These intersections were categorized into eight types based on number of legs (3 and 4), land use (urban or rural) and traffic control (signalized or minor stop-control). These categories were chosen to align with the intersection types in AASHTO’s recently released Highway Safety Manual (HSM). Geometric and traffic control elements were supplemented by compiling crash data and volumes on the major and minor approaches. The safety performance was analyzed by three primary methods. First, crash rates were calculated and analyzed for each of the intersection groups. Crash rates determined for Oregon intersections were generally well below rates found published for other states. Since it is unlikely that such a significant difference exists in the safety performance between states, it is more likely explanation is the different reporting thresholds and Oregon’s reliance on self-reporting. Second, crash patterns were tabulated for a number of crash and driver involved variables. These patterns, not before generated, will be very useful to improve identification of high crash intersection locations and improve diagnosis of these locations. Third, safety performance functions (SPFs) were created for intersections where sufficient data exist. For the purposes of this research SPFs were estimated for the rural 3-leg stop controlled and urban 4-leg signalized intersections. The SPFs developed in this modeling exercise were compared to the HSM base models calibrated to Oregon. The rural 3-leg stop models compare favorably. Within the volume range of the data used to generate the SPFs, the models compare well. The urban signalized intersection SPFs did not compare as well to the HSM base models. Further research is needed to investigate whether Oregon-specific SPFs have advantages over calibrated HSM models. The results of this analysis can be used to improve the diagnosis and identification of unusual safety performance at intersections in Oregon. The average rates are useful for peer comparisons and in calculation of critical rates. The crash patterns can be directly applied in diagnostic efforts to detect unusual patterns at intersections. The SPF modeling effort is the groundwork for further explorations and model development for Oregon facilities. Final report available online at: http://www.oregon.gov/odot/td/tp_res/docs/reports/2011/spr667_intersectionsafety.pdf