diff --git a/README.md b/README.md
index e1b77ea..c4aef14 100644
--- a/README.md
+++ b/README.md
@@ -25,7 +25,7 @@ def user_gene_function():
     return random.randint(1, 100)
 
 # The user defined Fitness Function
-def user_fitness_function():
+def user_fitness_function(chromosome):
     pass
 
 # Standard user size requirements
@@ -33,7 +33,7 @@ Population_size = 10
 Chromosome_length = 10
 
 # Create the Genetic algorithm
-ga = EasyGA.GA(Population_size, Chromosome_length,user_gene_function)
+ga = EasyGA.GA(Population_size, Chromosome_length,user_gene_function,user_fitness_function)
 ga.initialize()
 ```
 
diff --git a/src/EasyGA.py b/src/EasyGA.py
index 20d6e68..a6f2b10 100644
--- a/src/EasyGA.py
+++ b/src/EasyGA.py
@@ -62,7 +62,8 @@ class population:
         self.chromosomes.append(chromosome)
 
 class GA:
-    def __init__(self, population_size, chromosome_length, user_gene_function):
+    def __init__(self, population_size, chromosome_length,
+                    user_gene_function,user_fitness_function):
         # User defined variables
         self.population_size = population_size
         self.chromosome_length = chromosome_length
@@ -75,4 +76,6 @@ class GA:
 
     def initialize(self):
         # Create the initial population
-        self.population = self.initialization_impl.initialize(self.population_size, self.chromosome_length, self.user_gene_function)
+        self.population = self.initialization_impl.initialize(self.population_size,
+                                                                self.chromosome_length,
+                                                                 self.user_gene_function)
diff --git a/src/example.py b/src/example.py
index 98cb430..725cd78 100644
--- a/src/example.py
+++ b/src/example.py
@@ -6,7 +6,7 @@ def user_gene_function():
     return random.randint(1, 100)
 
 # The user defined Fitness Function
-def user_fitness_function():
+def user_fitness_function(chromosome):
     pass
 
 # Standard user size requirements
@@ -14,7 +14,8 @@ Population_size = 10
 Chromosome_length = 10
 
 # Create the Genetic algorithm
-ga = EasyGA.GA(Population_size, Chromosome_length,user_gene_function)
+ga = EasyGA.GA(Population_size, Chromosome_length,
+                user_gene_function,user_fitness_function)
 ga.initialize()
 
 # Looking to print the first Chromosome