Besides the feedstock composition, the highest treatment temperature (HTT) in pyrolysis is one of the key production parameters. The latter determines the feedstock’s carbonization extent, which influences physicochemical properties of the resulting biochar, and in consequence its performance in industrial and agricultural applications. The actual HTT of biomass is difficult to measure in a reliable manner in many large-scale pyrolysis units (e.g., rotary kilns). Therefore, producers and end-users often rely on unreliable or biased information regarding this key production parameter that affects biochar quality. Data from indirect chemical assessment methods of biochar’s carbonization extent correlate well with the highest treatment temperature. Therefore, this study demonstrates that the HTT can be accurately assessed posteriori and feedstock-independently via a simple-to-use model based on biochar characteristics related to the carbonization extent. For that purpose, 24 contrasting biochars from 12 different feedstocks produced in the most common production temperature range of 350-700 °C were analysed using 5 different established biochar chemical characterization methods. Then, experimental data was used to establish a multilinear regression model capable of correlating the HTT, which was successfully validated for external datasets. The correlation accuracy for biochars of various origin (lignocellulosic, manure) was satisfactorily high (R2adj. = 0.853, RSME =47 °C). The obtained correlation proved that the HTT can be predicted feedstock independently with the use of basic input data. It also provides a quick, simple, and reliable tool to verify the HTT of a given biochar.