Abstarct: Leaves are the primary photosynthetic organs and Leaf area production is one of important factors for energy transfer and accumulation of dry matter in crops. Leaf area is one of main variables which used to evaluate of growth, modeling and physiological-ecological processes such as photosynthesis, transpiration and energy balance and is a key variable for physiological studies, therefore accurate and simple models which determining leaf area of plants are important for many experimental comparisons. Nitrogen and carbon are elements that play key role in growth and development of plants. Therefore accurate and simple models determining leaf area of plants are important for many experimental comparisons , has important role in plant growth modeling. For this purpose, an experiment was carried out on shallot plant in research farm of Ferdowsi university of Mashhad in 2010. The experiment was conducted in factorial baxsed on random complete blocks design which treatments were nitrogen (100, 200, 250 and 300 kg ha-1) and weight of shallot bulb (10-20 g and 20-30 g) in 3 replication. For estimation of leaf area of this plant we measured the leaf dismensions [width (w) and length (L)], plant and leaf dry weight and the cumulative temperature was calculated using weather data. Various relationships including the model of the relationship between leaf dimension and leaf area, relationship between growth degree day and leaf area changes using the beta function, leaf area modeling with taking in to account the effect of carbon on the leaf area and creation relationships with leaf nitrogen input were employed to obtain the best model which can be used for estimating the area of individual of shallot leaves. Between all models studied in this experiment, LA=0/00005 (W2)2 +0/999(W2) + 0/0 by (R2 = 1, MSD = 0/0) provided the most accurate estimate, and by (R2 = 0/733, MSD = 92.724) showed the least estimate accuracy for shallot leaf area. the model which estimating effect of nitrogen on leaf area (R2=0.999, RMSE=4.49%) had higher accuracy than the model that estimating carbon effect (R2=0.733, RMSE=39.44%).