diff --git a/apps/probability/distribution/student_distribution.cpp b/apps/probability/distribution/student_distribution.cpp
index 39c510552..dd22a46ad 100644
--- a/apps/probability/distribution/student_distribution.cpp
+++ b/apps/probability/distribution/student_distribution.cpp
@@ -30,6 +30,9 @@ double StudentDistribution::cumulativeDistributiveFunctionAtAbscissa(double x) c
   if (x == 0.0) {
     return 0.5;
   }
+  if (std::isinf(x)) {
+    return 1.0;
+  }
   /* TODO There are some computation errors, where the probability falsly jumps to 1.
    * k = 0.001 and P(x < 42000000) (for 41000000 it is around 0.5)
    * k = 0.01 and P(x < 8400000) (for 41000000 it is around 0.6) */
diff --git a/poincare/src/normal_distribution.cpp b/poincare/src/normal_distribution.cpp
index aac8daaf8..7319341a4 100644
--- a/poincare/src/normal_distribution.cpp
+++ b/poincare/src/normal_distribution.cpp
@@ -83,18 +83,18 @@ bool NormalDistribution::ExpressionParametersAreOK(bool * result, const Expressi
 
 template<typename T>
 T NormalDistribution::StandardNormalCumulativeDistributiveFunctionAtAbscissa(T abscissa) {
-  if (std::isnan(abscissa) || std::isinf(abscissa)) {
+  if (std::isnan(abscissa)) {
     return NAN;
   }
+  if (std::isinf(abscissa) || abscissa > k_boundStandardNormalDistribution) {
+    return (T)1.0;
+  }
   if (abscissa == (T)0.0) {
     return (T)0.5;
   }
   if (abscissa < (T)0.0) {
     return ((T)1.0) - StandardNormalCumulativeDistributiveFunctionAtAbscissa(-abscissa);
   }
-  if (abscissa > k_boundStandardNormalDistribution) {
-    return (T)1.0;
-  }
   return ((T)0.5) + ((T)0.5) * std::erf(abscissa/std::sqrt(((T)2.0)));
 }