This study aims to evaluate the relationship between 33 variables that fit into the categories of roadway environment, crossing characteristics, population characteristics, and travel behavior with collision risk for pedestrians in City of San Diego using 14 years worth of collision data. The dependent variable, collision risk, measures the ratio of pedestrian collisions to pedestrian volume, controlling for exposure. 60 study sites were disaggregated to approach and departure sides, which resulted in an expanded sample of 342 study cases. This study examines both four-way intersections and mid-block crossings. A preliminary analysis found 13 significant variables, all with weak associations with the pedestrian risk variable. Based on these results, two models were created and analyzed: simple linear regression models with the 13 significant variables, and a multiple linear regression model utilizing all 33 independent variables. The multiple linear regression model found four variables to be significant (sidewalk width, posted speed, curb ramp not present, and informal crosswalk not passable), all with a positive association. The significant variables from both models belong into two categories of variables: variables that increase the amount of time a pedestrian spends crossing the street without separation from vehicle traffic, and variables that decrease visibility. Recommendations for future studies include utilizing a larger sample to increase the probability of achieving statistical significance. This study's inclusion of both mid-block and intersection sites increases the depth of understanding of pedestrian risk in the City of San Diego by more accurately reflecting the use of both intersection and mid-block crossing locations by pedestrians.