Improving corn (Zea mays L.) nitrogen (N) fertilizer rate recommendation tools should increase farmer’s profits and help mitigate N pollution. Weather and soil properties have repeatedly been shown to influence crop N need. The objective of this research was to improve publicly-available N recommendation tools by adjusting them with additional soil and weather information. Four N recommendation tools were evaluated across 49 N response trials conducted in eight U.S. states over three growing seasons. Tools were evaluated for split (planting+side-dress) fertilizer applications. Using an elastic net algorithm the difference between each tool’s N recommendation and the economically optimum N rate (EONR) was regressed against soil and weather information, then the elastic net regression coefficients were used to adjust the tool’s N recommendation. The evenness of rainfall calculated from planting to the date of sidedness and soil pH (0-0.30 m) were the most frequently identified parameters for adjusting tools. All tools showed improvement with adjustment (+r2 ≥ 0.09). The greatest improvement in tool performance was with including soil and weather information with the Late-Spring Soil Nitrate Test (LSNT), canopy reflectance sensing, and MRTN. This analysis demonstrated that incorporating soil and weather information can help improve N recommendations.