Two-photon absorption is the simultaneous absorption of two photons of light by a molecule. The molecular designs are limited due to the high cost of experimental screening quantum chemical calculations. Regarding this issue, an experiment was performed using 900 molecules, data was collected on TPACS (twophoton absorption and cross-section), molecular names, solvents, and TPACS measurement methods. Out of 900, 443 molecules have a single wavelength and one TPACS value and the other 486 molecules have different wavelengths and 2-11 TPACS values. This experiment shows that many molecules contain C, H, O, and N and are present in toluene. A molecular fragment fingerprinting method was used, in which molecular fragments were generated using a radius of 436 supported by the phyton toolkit that generates 546 features. Throughout the analysis, three types of models named Least absolute shrinkage and selection operator (LASSO), Gradient boosting regression tree (GBRT), and Extreme gradient boosting (XGB) were used. The studies revealed that the ML model prefers conjugation length over conjugation area and helped to check the effect of multipolar branched structure and quadrupolar linear structure on TPACS. SHAP (mathematical method to explain the prediction of machine learning models) helped to find a relation between conjugation length and TPACS and shows the impact of donor-acceptor groups on TPACS. SHAP value less than 0.05 have a minor effect on TPACS but a value greater than 0.5 have a beneficial effect. These features help to create an accurate ML model that can be used for experimental screening and quantum chemical calculations.