diff --git a/gtsam/nonlinear/NonlinearISAM-inl.h b/gtsam/nonlinear/NonlinearISAM-inl.h
index 4f9dafacc..83e483351 100644
--- a/gtsam/nonlinear/NonlinearISAM-inl.h
+++ b/gtsam/nonlinear/NonlinearISAM-inl.h
@@ -85,7 +85,7 @@ void NonlinearISAM<Values>::reorder_relinearize() {
 
 /* ************************************************************************* */
 template<class Values>
-Values NonlinearISAM<Values>::estimate() {
+Values NonlinearISAM<Values>::estimate() const {
   if(isam_.size() > 0)
     return linPoint_.expmap(optimize(isam_), ordering_);
   else
@@ -94,7 +94,7 @@ Values NonlinearISAM<Values>::estimate() {
 
 /* ************************************************************************* */
 template<class Values>
-Matrix NonlinearISAM<Values>::marginalCovariance(const Symbol& key) {
+Matrix NonlinearISAM<Values>::marginalCovariance(const Symbol& key) const {
 	Matrix covariance; Vector mean;
 	boost::tie(mean, covariance) = isam_.marginal(ordering_[key]);
 	return covariance;
diff --git a/gtsam/nonlinear/NonlinearISAM.h b/gtsam/nonlinear/NonlinearISAM.h
index 2b7a8a8e4..3178cba16 100644
--- a/gtsam/nonlinear/NonlinearISAM.h
+++ b/gtsam/nonlinear/NonlinearISAM.h
@@ -66,7 +66,7 @@ public:
 	void update(const Factors& newFactors, const Values& initialValues);
 
 	/** Return the current solution estimate */
-	Values estimate();
+	Values estimate() const;
 
 	/** Relinearization and reordering of variables */
 	void reorder_relinearize();
@@ -78,7 +78,7 @@ public:
 	void setOrdering(const Ordering& new_ordering) { ordering_ = new_ordering; }
 
 	/** find the marginal covariance for a single variable */
-	Matrix marginalCovariance(const Symbol& key);
+	Matrix marginalCovariance(const Symbol& key) const;
 
 	// access