Estimation of train delays is crucial for customer information. One cause of the train delays can be easily blamed on the weather. The effect of weather on signaling and dispatching can be indirectly articulated from the arrival and departure delays at the stations. The study uses Norwegian delay data from 2021, 2022 and parts of 2023. This data contains scheduled and actual departure and arrival times of trains on the Dovre line between Oslo and Trondheim. This article talks about acquiring freely available weather data using APIs at the stopping station and checking the effect of weather elements on the departure delay. Weather elements correlated with the departure delays were rainfall (precipitation) and temperature. This study attempts to articulate the quantitative nature of the effect of these weather elements on the departure delays of the trains. The delay prediction model uses different neural network algorithms. The prediction results from different algorithms are compared to provide a deeper insight into the effect of weather on the delay characteristics.