In a developing organism, tissue patterning relies extensively on mechanisms of cell-cell communication. This communication is regulated by a small group of receptor-mediated networks, most of which have been modeled extensively. However, the majority of the current models have been formulated at the molecular and cellular levels. We will discuss a modeling approach that accounts for the cell-cell communication necessary to pattern a developing tissue. In particular, we describe a parameter estimation scheme that helps answer otherwise experimentally inaccessible questions. The basic mechanism of tissue patterning involves a locally secreted ligand that spreads through the tissue, binding to and activating cell surface receptors, which control signal transduction and gene expression pathways in responding cells [1]. These processes contribute to the establishment of a concentration gradient of the ligand, or morphogen, in the extracellular environment. The responding cells interpret this signaling gradient in a concentration-dependent manner: cells nearest the morphogen source will decide to adopt different fates from those further away. This general patterning model, called the morphogen gradient model, occurs dozens of times in development of all animal species. However, direct in vivo measurements of morphogen concentration profiles have been few and far between. Here we show that our modeling approach, combined with indirect experimental measurements, allow us to quantitatively estimate the system's parameters, and thus predict the shape of morphogen profiles. As an example, we study the operation of the epidermal growth factor receptor (EGFR) network in embryonic development of Drosophila melanogaster, using the ventral ectoderm (VE) as a model tissue. In this tissue, the EGFR ligand Spitz is present in a concentration gradient, and its interactions with the receptor as well as a diffusible inhibitor (Argos) have been well characterized biochemically [2]. Our previously published model, which accounts for the known patterning in this tissue [3], uses these biochemical data in conjunction with the powerful tools of Drosophila genetics to quantitatively predict values of biophysical parameters, such as the diffusion lengths of the EGFR ligand Spitz and the inhibitor Argos. We propose further experiments to verify this modeling approach. [1] Martinez-Arias, A. and Stewart, A., Molecular principles of animal development. New York: Oxford University Press, 2002. [2] Klein, D.E., Nappi, V.M., Reeves, G.T., Shvartsman, S.Y., and Lemmon, M.A., Nature, 430: 1040-1044, 2004. [3] Reeves, G.T., Kalifa, R., Klein, D.E., Lemmon, M.A., and Shvartsman, S.Y., Dev. Biol., 284: 523-535, 2005.