Drought is one of Canada�s costliest natural disasters. Climate change is expected to increase the frequency, extent and intensity of droughts. Canada has an effective monitoring and reporting system for current conditions (known as the Canadian Drought Monitor) but forecasting future conditions has been limited by the analytical approach used to estimate drought severity and extent using multiple indicators, most calculated from station based data sets that have at minimum a 30 year historical record of data. In 2021, the Canadian Drought Outlook was developed using indicators calculated from the Global Ensemble Prediction System (GEPS) forecasts of precipitation and temperature data from the Meteorological Service of Canada. Indicators, including the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI) were calculated using historical weather station data combined with 32 day forecasts. These indicators were then used to train a Neural Network model to predict how the current Canadian Drought Monitor assessment will change over the course of a month. The drought outlook model runs on an ensemble forecasts then maps changes where there is at least a 50 percent chance of occurrence. Recent work is on expanding the number of indicators used to make these predictions using High Resolution Ensemble Land Surface Prediction system (HRELPS), which forecast both precipitation and temperature along with land surface variables at a 2.5 km resolution. Results indicated that coarse resolution forecasts (GEPS) show good agreement with drought monitor conditions.