This　paper　focuses　modeling　tumor　growth　with　cellular　automata.　A　one-dimensional　cellular　automaton　is　proposed　for　implementing　the　Gompertz　model　to　formulate　tumor　growth　dynamics,　which　is　called　Gompertz　CA.　First,　a　discrete　Gompertz　model　is　derived　from　the　standard　Gompertz　model.　And　then,　stochastically　evolutionary　rules　for　the　Gompertz　CA　are　developed　based　on　the　discrete　Gompertz　model.　The　Gompertz　CA　is　therefore　randomized　by　the　stochastically　evolutionary　rules　so　that　it　can　be　represented　with　a　stochastic　process　or　a　stochastic　difference　equation.