The knowledge gaps approached in this research are related to the dynamic modelling of the pickling process (the lack predictability and simplicity of the existing models) and to the process operation (its dependence on the initial conditions, such as the immersed surface, the immersed mass, and the corrosion inhibitor concentration). Original contributions regarding the identification of the optimum corrosion inhibitor concentration, the forecast of the corrosion rate and the appropriate timing for the acidic bath change, are offered with the help of a decision-making tool (PickT), developed, and verified with the help of measurements. Experiments consist in steel pickling (during 336h) in hydrochloric acid of industrial making (H2O:HCl, 1:1) with five different volumetric Cetilpyridinium bromide (CPB) as corrosion inhibitor. PickT has reliably and easy forecasted the corrosion rates, facilitating the estimation of the appropriate timing for the acidic bath change (250h) and of the optimum concentration of inhibitor of 12%. Results are in accordance with experimental findings. The tool advantages consist of the straightforward applicability, the low inputs requirements to make reliable forecasts and the accessibility for untrained professionals from the industry. From an industrial point of view, it supports decision to optimize the pickling process efficiency and facilitate cost savings: when to change the pickling solution, which is the optimum corrosion inhibitor addition, how much metal surface can be pickled using the same solution.