diff --git a/README.md b/README.md
index a2a88ecc0..59a78f164 100644
--- a/README.md
+++ b/README.md
@@ -57,7 +57,7 @@ print(ddsol, Val{true})
 ```
 Explicit Result
 Solution with 3 equations and 7 parameters.
-Returncode: sucess
+Returncode: success
 Sparsity: 7.0
 L2 Norm Error: 26.7343984476783
 AICC: 1.0013570199499398
diff --git a/src/solution.jl b/src/solution.jl
index 95830ec1a..b572b5506 100644
--- a/src/solution.jl
+++ b/src/solution.jl
@@ -185,7 +185,7 @@ function build_solution(prob::DataDrivenProblem, Ξ::AbstractMatrix, opt::Optimi
     sparsity = norm(Ξ, 0)
     sparsities = map(i->norm(i, 0), eachcol(Ξ))
 
-    retcode = size(Ξ, 2) == size(prob.DX, 1) ? :sucess : :incomplete
+    retcode = size(Ξ, 2) == size(prob.DX, 1) ? :success : :incomplete
     pnew = !isempty(parameters(b)) ? [prob.p; ps] : ps
     X = get_target(prob)
     Y = res_(prob.X, pnew, prob.t, prob.U)
@@ -252,7 +252,7 @@ function build_solution(prob::DataDrivenProblem, Ξ::AbstractMatrix, opt::Optimi
     sparsity = norm(Ξ, 0)
     sparsities = map(i->norm(i, 0), eachcol(Ξ))
 
-    retcode = size(Ξ, 2) == size(prob.DX, 1) ? :sucess : :incomplete
+    retcode = size(Ξ, 2) == size(prob.DX, 1) ? :success : :incomplete
     pnew = !isempty(parameters(b)) ? [prob.p; ps] : ps
     Y = res_([prob.X; prob.DX], pnew, prob.t, prob.U)
 
@@ -335,7 +335,7 @@ function build_solution(prob::DataDrivenProblem, k, C, B, Q, P, inds, b::Abstrac
         K = k, C = C, Q = Q, P = P, lift = b.f,
         eval_expression = eval_expression)
 
-    retcode = :sucess
+    retcode = :success
     X = get_target(prob)
     X_, p_, t, U = get_oop_args(prob)
 
diff --git a/src/symbolic_regression/occamnet.jl b/src/symbolic_regression/occamnet.jl
index 2812db462..1447bcf13 100644
--- a/src/symbolic_regression/occamnet.jl
+++ b/src/symbolic_regression/occamnet.jl
@@ -439,7 +439,7 @@ function build_solution(prob::DataDrivenProblem, net::OccamNet, o::OccamSR, opt;
     # Build the metrics
     pb = exp(sum(logprobability(net, route)))
     pbs = probability(net, route)
-    retcode = pb > 0.5 ? :sucess : :unlikely
+    retcode = pb > 0.5 ? :success : :unlikely
 
     error = norm(X-Y, 2)
     k = free_parameters(res_)
diff --git a/src/symbolic_regression/symbolic_regression.jl b/src/symbolic_regression/symbolic_regression.jl
index 1bac11aaa..aa8b8f067 100644
--- a/src/symbolic_regression/symbolic_regression.jl
+++ b/src/symbolic_regression/symbolic_regression.jl
@@ -92,7 +92,7 @@ function build_solution(prob::AbstractDataDrivenProblem, alg::EQSearch, doms; ev
     # Build the metrics
     complexities = map(x->countNodes(x[end].tree), doms)
     complexity = sum(complexities)
-    retcode = :sucess
+    retcode = :success
 
     error = norm(X-Y, 2)
     k = free_parameters(res_)