High-quality data and reliable analytical methods are the foundation of data-driven decision-making. There are various data-driven safety analysis methods for identifying sites with promise and for predicting crash frequency for project design-level analysis. Using more reliable methods, agencies such as the Ohio Department of Transportation (ODOT) maximize the opportunity to reduce crashes or crash severity outcomes by identifying sites with the greatest potential for improvement and allocating resources to achieve the greatest return on investment. ODOT engaged in developing Ohio-specific planning-level and project design-level safety performance functions (SPFs) to improve reliability for network screening and prediction of safety performance for project design alternatives on freeway segments. This presentation will include information on the processes used to develop these Ohio-specific SPFs, the findings and recommendations for their utilization with Safety Analyst, the Economic Crash Analysis Tool and other aspects of the Highway Safety Manual.