The goal is to create regression models estimating the daily Penman–Monteith reference evapotranspiration (PMR) using latitude–temperature for the state of Sinaloa. The reference evapotranspiration was calculated (1979–2017) by the methods of Penman–Monteith using empirical equations (PMC), Hargreaves (HAC), and PMR. Prior to calculating PMC, the incident solar radiation (SR) was calculated. From the Acaponeta station (2005–2008, 2011–2013, and 2015–2017), all complete observed variables were obtained: mean temperature, incident solar radiation (SRg), average relative humidity, and average wind speed at a height of 10 m. The data from the eight weather stations were provided by the National Meteorological Service and the National Water Commission. The daily observed Penman–Monteith reference evapotranspiration (PMO) was calculated. For validation, three simple linear regressions (SLR) were applied: SR vs SRg, PMC vs PMO, and PMR vs PMO hypothesis tests were applied to each SLR: Pearson correlation (Pr) vs critical Pearson correlation (Pcr). All rP were significantly different from zero (> |0.576|): SRg vs SR (Pr = 0.951), PMC vs PMO ( Pr = 0 .592), and PMR vs PMO (Pr = 0.625). This study provides new models that can motivate and support intelligent irrigation in “the breadbasket of Mexico.”