diff --git a/src/linear/logistic_regression.rs b/src/linear/logistic_regression.rs
index cbdef77..a23c15a 100644
--- a/src/linear/logistic_regression.rs
+++ b/src/linear/logistic_regression.rs
@@ -68,10 +68,21 @@ use crate::optimization::first_order::{FirstOrderOptimizer, OptimizerResult};
 use crate::optimization::line_search::Backtracking;
 use crate::optimization::FunctionOrder;
 
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[derive(Debug, Clone)]
+/// Solver options for Logistic regression. Right now only LBFGS solver is supported.
+pub enum LogisticRegressionSolverName {
+    /// Limited-memory Broyden–Fletcher–Goldfarb–Shanno method, see [LBFGS paper](http://users.iems.northwestern.edu/~nocedal/lbfgsb.html)
+    LBFGS,
+}
+
 /// Logistic Regression parameters
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
 #[derive(Debug, Clone)]
-pub struct LogisticRegressionParameters {}
+pub struct LogisticRegressionParameters {
+    /// Solver to use for estimation of regression coefficients.
+    pub solver: LogisticRegressionSolverName,
+}
 
 /// Logistic Regression
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
@@ -105,9 +116,19 @@ struct BinaryObjectiveFunction<'a, T: RealNumber, M: Matrix<T>> {
     phantom: PhantomData<&'a T>,
 }
 
+impl LogisticRegressionParameters {
+    /// Solver to use for estimation of regression coefficients.
+    pub fn with_solver(mut self, solver: LogisticRegressionSolverName) -> Self {
+        self.solver = solver;
+        self
+    }
+}
+
 impl Default for LogisticRegressionParameters {
     fn default() -> Self {
-        LogisticRegressionParameters {}
+        LogisticRegressionParameters {
+            solver: LogisticRegressionSolverName::LBFGS,
+        }
     }
 }