Chemistry is a very structured domain where there are either a lot of experimental data and knowledge available. Unfortunately, not all cases are such. There are real world scenarios where data is scarce and expensive.
Predictions are not the holy grail when you want to optimize the production process. Characteristics of the process are the ones that are of the most interest. Bayesian approach allows to get insights from scarce data, and conclude on relations strength driving informed data driven decision making.