Temperature and soil moisture are the two main factors that determine weed emergence. Therefore, hydrothermal models were applied to predict weed emergence. These models apply the germination parameters of a particular species to predict emergence: base temperature (Tb)—the minimum temperature required for germination—and the base water potential (Ψb)— the lowest value of soil water potential at which the seeds of a given species germinate. As part of the doctoral research, the values of germination parameters of seven economically important weed species in maize were estimated under laboratory conditions. Then, during two growing years (2019 and 2020, respectively), the emergence of the weed species Echinochloa crus-galli was monitored in maize at Šašinovečki Lug (45°50’59.6 “N 16°09’53.9 “E) to validate the Italian hydrothermal model AlertInf. The following Tb and Ψb were estimated: Ambrosia artemisiifolia (1.5°C; -0.89 MPa), Chenopodium album (3.4°C; -1.38 MPa), Abutilon theophrasti (4.5°C; -0.67 MPa), Setaria pumila (6.6°C; -0.71 MPa), Echinochloa crus-galli (10.8°C; -0.97 MPa),
Panicum capillare (11.0°C; -0.87 MPa), and Amaranthus retroflexus (13.9°C; -0.36 MPa). The calibrated AlertInf model successfully predicted the emergence of the weed species Echinochloa crus-galli. The overall performance of the model was evaluated by the root mean square error (RMSE = 1.69 in 2019 and 1.38 in 2020) and the modeling efficiency index (EF = 0.97 for 2019 and 0.98 for 2020). A successful prediction of weed emergence in continental Croatia while applying the AlertInf model developed in Italy is of importance for potential research on the extension of this model to other geographical areas and other weed maize species.