Most biological systems are so complex they preclude any reasonable description of them in terms of the basic interactions among their fundamental constituents. For this reason application of statistical physics of disordered systems, in particular percolation theory, to biological problems has thus far been relatively limited. But there are biological processes that are particularly statistical in nature and in which the role of connectivity of different elements or constituents is prominent. Examples include self-assembly of tobacco mosaic and other simple viruses (see, e.g., Hohn and Hohn 1970), actin filaments (Poglazov et al. 1967) and flagella (Asakura et al. 1968), lymphocyte patch and cap formation (Karnovsky et al. 1972), and many precipitation and agglutination phenomena. Some of these phenomena, such as precipitation, occur spontaneously if the functional groups are sufficiently reactive. Thus, these phenomena depend on their level of chemical complexity and that of the solvent in which they occur. Other factors are not directly related to the solvent but have great influence on the outcome of biological processes. For example, in antigen-antibody reactions, clusters of all sizes react with one another forming complex branched networks, which grow in size as time progresses. We may also have reactions which can proceed by rapid addition of monomers to growing chains after a slow initiating event. These processes are therefore similar to percolation processes. This chapter discusses application of percolation concepts to such phenomena. We start with a discussion of antigen-antibody reactions and aggregations, then discuss a few other biological processes to which percolation may be relevant.