Underestimation or overestimating activities’ duration in construction projects leads to many problems like lack of funding or procrastination. However, estimating duration accurately for construction projects is difficult because of many factors like identified and unidentified negative risks. This paper tried to estimate realistic durations of steel framing activities in a high-rise building using a combination of Artificial Neural Networks (ANNs) and fuzzy logic algorithms with data from five similar projects. Initial planned durations and the top five pure risks are the inputs, and estimated actual durations are the outputs. The data from the first four projects was for training, and the fifth one was for simulation. Then, the estimated expected actual durations under uncertainties are compared to the actual durations of the project. The results showed that about 75% of the fifth project’s activities had errors of less than three days compared to the actual durations.