Abstract While CRISPR has revolutionized biotechnology, predicting CRISPR-Cas nuclease activity remains a challenge. Herein, through the trans-cleavage feature of CRISPR-Cas12a, we investigate the correlation between CRISPR enzyme kinetics and the free energy change of crRNA and DNA targets from their initial thermodynamic states to a presumed transition state before hybridization. By subjecting computationally designed CRISPR RNAs (crRNAs), we unravel a linear correlation between the trans-cleavage kinetics of Cas12a and the energy barrier for crRNA spacer and single-stranded DNA target unwinding. This correlation shifts to a parabolic relationship with the energy consumption required for double-stranded DNA target separation. We further validate these correlations using ∼100 randomly selected crRNA/DNA pairs from viral genomes. Through machine learning methods, we reveal the synergistic effect of free energy change of crRNA and DNA on categorizing Cas12a activity on a two-dimensional map. Furthermore, by examining other potential factors, we find that the free energy change is the predominant factor governing Cas12a kinetics. This study will not only empower sequence design for numerous applications of CRISPR-Cas12a systems, but can also extend to activity prediction for a variety of enzymatic reactions driven by nucleic acid dynamics.