Abstract Production planning is a problem at CV. Pandu Kencana Jombang, where the production quantity of Timba Cor TC is not planned ahead of the production process but is instead determined statically or based on warehouse stock without considering sales dynamics. The author proposes a solution by implementing the Triple Exponential Smoothing forecasting method. This well-known adaptive method is used for time series modeling and involves three levels of smoothing: overall, trend, and seasonal smoothing. Before forecasting the production and sales of TC Cor Lead for Week 1 of April 2022, an alpha value with the smallest error percentage is required. To find this, data from August 2021 to March 2022 is used for forecasting, applying alpha values from 0.1 to 0.9, and calculating the MAPE (mean absolute percentage error) for each. Once the alpha with the smallest MAPE is found, it is used to predict Week 1 of April 2022. The study results show that the Triple Exponential Smoothing method successfully predicted the production and sales with 97.7% accuracy and a 6.3% MAPE for production, and 93.7% accuracy with a 6.3% MAPE for sales. Keywords: forecasting, planning, triple exponential smoothing