Historical rainfall data from 1997-2016 of Juba County, South Sudan were used in a Feed-Forward Neural Network (FFNN) model to make future predictions. Annual rainfall data were aggregated into three seasons MAMJ, JAS and OND and later trained for best forecasts for the period 2017-2034 using the Alyuda Forecaster XL software. Best training of the time series was attained, once the minimum error of the weight expressed as MSE or AE between the measured variable and predicted was achieved during gradient descent. The results showed that for MAMJ and JAS months, the number forecasts were over 85% whereas this was between 60-80% for OND months. The Seasonal Kendal (SK) test on future rainfall forecasts as well as the Theil-Sen slope showed negative monotonic trends in the mean values till the end of 2034 of all three seasons with MAMJ, JAS at OND at 100, 150 and 80 mm respectively. Rainfall forecast showed that the MAMJ months for the years 2019 to 2027 will be moderately wet except in April 2021 which will experience some severe wetness (due to intensive rainfall). Interdecadal severe drought with less than 60, 100 and 10 mm for MAMJ, JAS and OND respectively, is expected between 2028 to 2033 after almost two decades. The declining onset of MAMJ rains is expected to significantly affect the timing for land preparation and crop planting.